iarcuschin
commited on
Commit
•
39e7304
1
Parent(s):
9661ddf
Update metadata files
Browse files- benchmark_cases_metadata.csv +19 -19
- benchmark_cases_metadata.parquet +2 -2
- benchmark_metadata.json +387 -154
- benchmark_metadata_croissant.json +1103 -0
benchmark_cases_metadata.csv
CHANGED
@@ -1,19 +1,19 @@
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case_id,task_description,max_seq_len,min_seq_len,training_args.atol,training_args.lr,training_args.use_single_loss,training_args.iit_weight,training_args.behavior_weight,training_args.strict_weight,training_args.epochs,training_args.act_fn,training_args.clip_grad_norm,training_args.lr_scheduler,transformer_cfg.n_layers,transformer_cfg.d_model,transformer_cfg.n_ctx,transformer_cfg.d_head,transformer_cfg.model_name,transformer_cfg.n_heads,transformer_cfg.d_mlp,transformer_cfg.act_fn,transformer_cfg.d_vocab,transformer_cfg.eps,transformer_cfg.use_attn_result,transformer_cfg.use_attn_scale,transformer_cfg.use_split_qkv_input,transformer_cfg.use_hook_mlp_in,transformer_cfg.use_attn_in,transformer_cfg.use_local_attn,transformer_cfg.original_architecture,transformer_cfg.from_checkpoint,transformer_cfg.checkpoint_index,transformer_cfg.checkpoint_label_type,transformer_cfg.checkpoint_value,transformer_cfg.tokenizer_name,transformer_cfg.window_size,transformer_cfg.attn_types,transformer_cfg.init_mode,transformer_cfg.normalization_type,transformer_cfg.device,transformer_cfg.n_devices,transformer_cfg.attention_dir,transformer_cfg.attn_only,transformer_cfg.seed,transformer_cfg.initializer_range,transformer_cfg.init_weights,transformer_cfg.scale_attn_by_inverse_layer_idx,transformer_cfg.positional_embedding_type,transformer_cfg.final_rms,transformer_cfg.d_vocab_out,transformer_cfg.parallel_attn_mlp,transformer_cfg.rotary_dim,transformer_cfg.n_params,transformer_cfg.use_hook_tokens,transformer_cfg.gated_mlp,transformer_cfg.default_prepend_bos,transformer_cfg.dtype,transformer_cfg.tokenizer_prepends_bos,transformer_cfg.n_key_value_heads,transformer_cfg.post_embedding_ln,transformer_cfg.rotary_base,transformer_cfg.trust_remote_code,transformer_cfg.rotary_adjacent_pairs
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11,Counts the number of words in a sequence based on their length.,10
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13,"Analyzes the trend (increasing, decreasing, constant) of numeric tokens.",10
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18,"Classify each token based on its frequency as 'rare', 'common', or 'frequent'.",10
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19,Removes consecutive duplicate tokens from a sequence.,15
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20,Detect spam messages based on appearance of spam keywords.,10
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21,Extract unique tokens from a string,10
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24,Identifies the first occurrence of each token in a sequence.,10
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3,Returns the fraction of 'x' in the input up to the i-th position for all i.,5
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33,Checks if each token's length is odd or even.,10
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34,Calculate the ratio of vowels to consonants in each word.,10
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35,Alternates capitalization of each character in words.,10
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36,"Classifies each token as 'positive', 'negative', or 'neutral' based on emojis.",10
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37,Reverses each word in the sequence except for specified exclusions.,10
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38,Checks if tokens alternate between two types.,10
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4,Return fraction of previous open tokens minus the fraction of close tokens.,10
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8,Fills gaps between tokens with a specified filler.,10
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ioi
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ioi_next_token
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case_id,url,task_description,max_seq_len,min_seq_len,training_args.atol,training_args.lr,training_args.use_single_loss,training_args.iit_weight,training_args.behavior_weight,training_args.strict_weight,training_args.epochs,training_args.act_fn,training_args.clip_grad_norm,training_args.lr_scheduler,transformer_cfg.n_layers,transformer_cfg.d_model,transformer_cfg.n_ctx,transformer_cfg.d_head,transformer_cfg.model_name,transformer_cfg.n_heads,transformer_cfg.d_mlp,transformer_cfg.act_fn,transformer_cfg.d_vocab,transformer_cfg.eps,transformer_cfg.use_attn_result,transformer_cfg.use_attn_scale,transformer_cfg.use_split_qkv_input,transformer_cfg.use_hook_mlp_in,transformer_cfg.use_attn_in,transformer_cfg.use_local_attn,transformer_cfg.original_architecture,transformer_cfg.from_checkpoint,transformer_cfg.checkpoint_index,transformer_cfg.checkpoint_label_type,transformer_cfg.checkpoint_value,transformer_cfg.tokenizer_name,transformer_cfg.window_size,transformer_cfg.attn_types,transformer_cfg.init_mode,transformer_cfg.normalization_type,transformer_cfg.device,transformer_cfg.n_devices,transformer_cfg.attention_dir,transformer_cfg.attn_only,transformer_cfg.seed,transformer_cfg.initializer_range,transformer_cfg.init_weights,transformer_cfg.scale_attn_by_inverse_layer_idx,transformer_cfg.positional_embedding_type,transformer_cfg.final_rms,transformer_cfg.d_vocab_out,transformer_cfg.parallel_attn_mlp,transformer_cfg.rotary_dim,transformer_cfg.n_params,transformer_cfg.use_hook_tokens,transformer_cfg.gated_mlp,transformer_cfg.default_prepend_bos,transformer_cfg.dtype,transformer_cfg.tokenizer_prepends_bos,transformer_cfg.n_key_value_heads,transformer_cfg.post_embedding_ln,transformer_cfg.rotary_base,transformer_cfg.trust_remote_code,transformer_cfg.rotary_adjacent_pairs
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11,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/11,Counts the number of words in a sequence based on their length.,10,4,0.05,0.01,False,1.0,1.0,0.4,500.0,gelu,1.0,,2.0,12.0,10.0,3.0,custom,4.0,48.0,gelu,10.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.1460593486680443,True,False,standard,False,5.0,False,,3456.0,False,False,True,torch.float32,,,False,10000.0,False,False
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13,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/13,"Analyzes the trend (increasing, decreasing, constant) of numeric tokens.",10,4,0.05,0.01,False,1.0,1.0,0.4,500.0,gelu,1.0,,2.0,20.0,10.0,5.0,custom,4.0,80.0,gelu,5.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,bidirectional,False,0.0,0.1460593486680443,True,False,standard,False,3.0,False,,9600.0,False,False,True,torch.float32,,,False,10000.0,False,False
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18,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/18,"Classify each token based on its frequency as 'rare', 'common', or 'frequent'.",10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,12.0,10.0,3.0,custom,4.0,48.0,gelu,7.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,bidirectional,False,0.0,0.12344267996967354,True,False,standard,False,3.0,False,,3456.0,False,False,True,torch.float32,,,False,10000.0,False,False
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19,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/19,Removes consecutive duplicate tokens from a sequence.,15,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,32.0,15.0,8.0,custom,4.0,128.0,gelu,5.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.15689290811054724,True,False,standard,False,3.0,False,,24576.0,False,False,True,torch.float32,,,False,10000.0,False,False
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20,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/20,Detect spam messages based on appearance of spam keywords.,10,4,0.05,0.001,False,1.0,1.0,1.0,2000.0,gelu,0.1,,2.0,4.0,10.0,1.0,custom,4.0,16.0,gelu,14.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cuda,1.0,causal,False,0.0,0.16,True,False,standard,False,2.0,False,,384.0,False,False,True,torch.float32,,,False,10000.0,False,False
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21,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/21,Extract unique tokens from a string,10,4,0.05,0.01,False,1.0,1.0,0.4,500.0,gelu,1.0,,2.0,20.0,10.0,5.0,custom,4.0,80.0,gelu,5.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.1885618083164127,True,False,standard,False,3.0,False,,9600.0,False,False,True,torch.float32,,,False,10000.0,False,False
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24,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/24,Identifies the first occurrence of each token in a sequence.,10,4,0.05,0.01,False,1.0,1.0,0.4,500.0,gelu,1.0,,2.0,20.0,10.0,5.0,custom,4.0,80.0,gelu,5.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.1885618083164127,True,False,standard,False,3.0,False,,9600.0,False,False,True,torch.float32,,,False,10000.0,False,False
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3,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/3,Returns the fraction of 'x' in the input up to the i-th position for all i.,5,4,0.05,0.001,False,1.0,1.0,10.0,2000.0,gelu,0.1,,2.0,12.0,5.0,3.0,custom,4.0,48.0,gelu,6.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.22188007849009167,True,False,standard,False,1.0,False,,3456.0,False,False,True,torch.float32,,,False,10000.0,False,False
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33,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/33,Checks if each token's length is odd or even.,10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,4.0,10.0,1.0,custom,4.0,16.0,gelu,10.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.17457431218879393,True,False,standard,False,2.0,False,,384.0,False,False,True,torch.float32,,,False,10000.0,False,False
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34,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/34,Calculate the ratio of vowels to consonants in each word.,10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,4.0,10.0,1.0,custom,4.0,16.0,gelu,10.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.16329931618554522,True,False,standard,False,5.0,False,,384.0,False,False,True,torch.float32,,,False,10000.0,False,False
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35,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/35,Alternates capitalization of each character in words.,10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,4.0,10.0,1.0,custom,4.0,16.0,gelu,10.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.1539600717839002,True,False,standard,False,8.0,False,,384.0,False,False,True,torch.float32,,,False,10000.0,False,False
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36,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/36,"Classifies each token as 'positive', 'negative', or 'neutral' based on emojis.",10,4,0.05,0.001,False,1.0,1.0,10.0,2000.0,gelu,0.1,,2.0,4.0,10.0,1.0,custom,4.0,16.0,gelu,5.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cuda,1.0,causal,False,0.0,0.19402850002906638,True,False,standard,False,3.0,False,,384.0,False,False,True,torch.float32,,,False,10000.0,False,False
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37,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/37,Reverses each word in the sequence except for specified exclusions.,10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,4.0,10.0,1.0,custom,4.0,16.0,gelu,10.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.1539600717839002,True,False,standard,False,8.0,False,,384.0,False,False,True,torch.float32,,,False,10000.0,False,False
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38,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/38,Checks if tokens alternate between two types.,10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,20.0,10.0,5.0,custom,4.0,80.0,gelu,5.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.1539600717839002,True,False,standard,False,2.0,False,,9600.0,False,False,True,torch.float32,,,False,10000.0,False,False
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4,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/4,Return fraction of previous open tokens minus the fraction of close tokens.,10,4,0.05,0.001,False,1.0,1.0,0.4,2000.0,gelu,0.1,,2.0,20.0,10.0,5.0,custom,4.0,80.0,gelu,7.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.17056057308448835,True,False,standard,False,1.0,False,,9600.0,False,False,True,torch.float32,,,False,10000.0,False,False
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8,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/8,Fills gaps between tokens with a specified filler.,10,4,0.05,0.01,False,1.0,1.0,0.4,500.0,gelu,1.0,,2.0,20.0,10.0,5.0,custom,4.0,80.0,gelu,10.0,1e-05,True,True,True,True,False,False,,False,,,,,,,gpt2,,cpu,1.0,causal,False,0.0,0.13333333333333333,True,False,standard,False,8.0,False,,9600.0,False,False,True,torch.float32,,,False,10000.0,False,False
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ioi,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/ioi,Indirect object identification,16,16,,,True,,,,,,,,,,,,,,,,,,True,True,True,True,True,True,,True,,,,,,,,,,,,True,,,True,True,,True,,True,,,True,True,True,,,,True,,True,True
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ioi_next_token,https://huggingface.co/cybershiptrooper/InterpBench/tree/main/ioi_next_token,Indirect object identification,16,16,,,True,,,,,,,,,,,,,,,,,,True,True,True,True,True,True,,True,,,,,,,,,,,,True,,,True,True,,True,,True,,,True,True,True,,,,True,,True,True
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benchmark_cases_metadata.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:12652b82dbded2521f44e1219ade14c88e6bd787db5a2141803db257fb375e87
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size 51034
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benchmark_metadata.json
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"name": "InterpBench",
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"version": "1.0.0",
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"description": "A benchmark of transformers with known circuits for evaluating mechanistic interpretability techniques.",
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"cases": [
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{
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"case_id": "11",
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"
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"edges.pkl",
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"meta_510.json"
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],
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"task_description": "Counts the number of words in a sequence based on their length.",
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"vocab": [
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"J",
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"
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"poiVg",
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"V",
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],
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"max_seq_len": 10,
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"min_seq_len": 4,
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"transformer_cfg": {
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"n_layers": 2,
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"d_model": 12,
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"case_id": "13",
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"task_description": "Analyzes the trend (increasing, decreasing, constant) of numeric tokens.",
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"max_seq_len": 10,
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],
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"task_description": "Classify each token based on its frequency as 'rare', 'common', or 'frequent'.",
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"vocab": [
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"e",
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"max_seq_len": 10,
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"min_seq_len": 4,
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"task_description": "Removes consecutive duplicate tokens from a sequence.",
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"vocab": [
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"c"
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"max_seq_len": 15,
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"min_seq_len": 4,
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"task_description": "Detect spam messages based on appearance of spam keywords.",
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"vocab": [
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"J",
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"max_seq_len": 10,
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"min_seq_len": 4,
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"transformer_cfg": {
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"n_layers": 2,
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"d_model": 4,
|
@@ -426,20 +493,33 @@
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},
|
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{
|
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"case_id": "21",
|
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-
"
|
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"edges.pkl",
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"ll_model_510.pth",
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-
"ll_model_cfg_510.pkl",
|
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-
"meta_510.json"
|
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-
],
|
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"task_description": "Extract unique tokens from a string",
|
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"vocab": [
|
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-
"b",
|
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"a",
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"c"
|
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],
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"max_seq_len": 10,
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"min_seq_len": 4,
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"transformer_cfg": {
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"n_layers": 2,
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"d_model": 20,
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@@ -507,20 +587,33 @@
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},
|
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{
|
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"case_id": "24",
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-
"
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"edges.pkl",
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"ll_model_510.pth",
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"ll_model_cfg_510.pkl",
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"meta_510.json"
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-
],
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"task_description": "Identifies the first occurrence of each token in a sequence.",
|
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"vocab": [
|
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-
"b",
|
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"a",
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"c"
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],
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"max_seq_len": 10,
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"min_seq_len": 4,
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"transformer_cfg": {
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"n_layers": 2,
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"d_model": 20,
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@@ -588,21 +681,34 @@
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},
|
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{
|
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"case_id": "3",
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-
"
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"edges.pkl",
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"ll_model_10110.pth",
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"ll_model_cfg_10110.pkl",
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"meta_10110.json"
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-
],
|
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"task_description": "Returns the fraction of 'x' in the input up to the i-th position for all i.",
|
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"vocab": [
|
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-
"x",
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-
"b",
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"a",
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-
"
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],
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"max_seq_len": 5,
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"min_seq_len": 4,
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"transformer_cfg": {
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"n_layers": 2,
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"d_model": 12,
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@@ -670,25 +776,38 @@
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},
|
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{
|
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"case_id": "33",
|
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-
"
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-
"edges.pkl",
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-
"ll_model_510.pth",
|
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-
"ll_model_cfg_510.pkl",
|
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-
"meta_510.json"
|
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-
],
|
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"task_description": "Checks if each token's length is odd or even.",
|
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"vocab": [
|
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"J",
|
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-
"
|
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-
"
|
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-
"poiVg",
|
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"V",
|
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"b",
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-
"
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-
"
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],
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"max_seq_len": 10,
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"min_seq_len": 4,
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"transformer_cfg": {
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"n_layers": 2,
|
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"d_model": 4,
|
@@ -756,25 +875,38 @@
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|
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},
|
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{
|
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"case_id": "34",
|
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-
"
|
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-
"edges.pkl",
|
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-
"ll_model_510.pth",
|
762 |
-
"ll_model_cfg_510.pkl",
|
763 |
-
"meta_510.json"
|
764 |
-
],
|
765 |
"task_description": "Calculate the ratio of vowels to consonants in each word.",
|
766 |
"vocab": [
|
767 |
"J",
|
768 |
-
"
|
769 |
-
"
|
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-
"poiVg",
|
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"V",
|
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"b",
|
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-
"
|
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-
"
|
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|
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],
|
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"max_seq_len": 10,
|
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"min_seq_len": 4,
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"transformer_cfg": {
|
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"n_layers": 2,
|
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"d_model": 4,
|
@@ -842,25 +974,38 @@
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|
842 |
},
|
843 |
{
|
844 |
"case_id": "35",
|
845 |
-
"
|
846 |
-
"edges.pkl",
|
847 |
-
"ll_model_510.pth",
|
848 |
-
"ll_model_cfg_510.pkl",
|
849 |
-
"meta_510.json"
|
850 |
-
],
|
851 |
"task_description": "Alternates capitalization of each character in words.",
|
852 |
"vocab": [
|
853 |
"J",
|
854 |
-
"
|
855 |
-
"
|
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-
"poiVg",
|
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"V",
|
858 |
"b",
|
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-
"
|
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-
"
|
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|
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],
|
862 |
"max_seq_len": 10,
|
863 |
"min_seq_len": 4,
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|
864 |
"transformer_cfg": {
|
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"n_layers": 2,
|
866 |
"d_model": 4,
|
@@ -928,20 +1073,33 @@
|
|
928 |
},
|
929 |
{
|
930 |
"case_id": "36",
|
931 |
-
"
|
932 |
-
"edges.pkl",
|
933 |
-
"ll_model_10110.pth",
|
934 |
-
"ll_model_cfg_10110.pkl",
|
935 |
-
"meta_10110.json"
|
936 |
-
],
|
937 |
"task_description": "Classifies each token as 'positive', 'negative', or 'neutral' based on emojis.",
|
938 |
"vocab": [
|
939 |
-
"\ud83d\ude22",
|
940 |
"\ud83d\udcd8",
|
941 |
-
"\ud83d\ude0a"
|
|
|
942 |
],
|
943 |
"max_seq_len": 10,
|
944 |
"min_seq_len": 4,
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|
945 |
"transformer_cfg": {
|
946 |
"n_layers": 2,
|
947 |
"d_model": 4,
|
@@ -1009,25 +1167,38 @@
|
|
1009 |
},
|
1010 |
{
|
1011 |
"case_id": "37",
|
1012 |
-
"
|
1013 |
-
"edges.pkl",
|
1014 |
-
"ll_model_510.pth",
|
1015 |
-
"ll_model_cfg_510.pkl",
|
1016 |
-
"meta_510.json"
|
1017 |
-
],
|
1018 |
"task_description": "Reverses each word in the sequence except for specified exclusions.",
|
1019 |
"vocab": [
|
1020 |
"J",
|
1021 |
-
"
|
1022 |
-
"
|
1023 |
-
"poiVg",
|
1024 |
"V",
|
1025 |
"b",
|
1026 |
-
"
|
1027 |
-
"
|
|
|
1028 |
],
|
1029 |
"max_seq_len": 10,
|
1030 |
"min_seq_len": 4,
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|
1031 |
"transformer_cfg": {
|
1032 |
"n_layers": 2,
|
1033 |
"d_model": 4,
|
@@ -1095,20 +1266,33 @@
|
|
1095 |
},
|
1096 |
{
|
1097 |
"case_id": "38",
|
1098 |
-
"
|
1099 |
-
"edges.pkl",
|
1100 |
-
"ll_model_510.pth",
|
1101 |
-
"ll_model_cfg_510.pkl",
|
1102 |
-
"meta_510.json"
|
1103 |
-
],
|
1104 |
"task_description": "Checks if tokens alternate between two types.",
|
1105 |
"vocab": [
|
1106 |
-
"b",
|
1107 |
"a",
|
|
|
1108 |
"c"
|
1109 |
],
|
1110 |
"max_seq_len": 10,
|
1111 |
"min_seq_len": 4,
|
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|
1112 |
"transformer_cfg": {
|
1113 |
"n_layers": 2,
|
1114 |
"d_model": 20,
|
@@ -1176,22 +1360,35 @@
|
|
1176 |
},
|
1177 |
{
|
1178 |
"case_id": "4",
|
1179 |
-
"
|
1180 |
-
"edges.pkl",
|
1181 |
-
"ll_model_510.pth",
|
1182 |
-
"ll_model_cfg_510.pkl",
|
1183 |
-
"meta_510.json"
|
1184 |
-
],
|
1185 |
"task_description": "Return fraction of previous open tokens minus the fraction of close tokens.",
|
1186 |
"vocab": [
|
1187 |
-
"b",
|
1188 |
"(",
|
1189 |
-
"c",
|
1190 |
")",
|
1191 |
-
"a"
|
|
|
|
|
1192 |
],
|
1193 |
"max_seq_len": 10,
|
1194 |
"min_seq_len": 4,
|
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|
1195 |
"transformer_cfg": {
|
1196 |
"n_layers": 2,
|
1197 |
"d_model": 20,
|
@@ -1259,25 +1456,38 @@
|
|
1259 |
},
|
1260 |
{
|
1261 |
"case_id": "8",
|
1262 |
-
"
|
1263 |
-
"edges.pkl",
|
1264 |
-
"ll_model_510.pth",
|
1265 |
-
"ll_model_cfg_510.pkl",
|
1266 |
-
"meta_510.json"
|
1267 |
-
],
|
1268 |
"task_description": "Fills gaps between tokens with a specified filler.",
|
1269 |
"vocab": [
|
1270 |
"J",
|
1271 |
-
"
|
1272 |
-
"
|
1273 |
-
"poiVg",
|
1274 |
"V",
|
1275 |
"b",
|
1276 |
-
"
|
1277 |
-
"
|
|
|
1278 |
],
|
1279 |
"max_seq_len": 10,
|
1280 |
"min_seq_len": 4,
|
|
|
|
|
|
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|
|
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|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
1281 |
"transformer_cfg": {
|
1282 |
"n_layers": 2,
|
1283 |
"d_model": 20,
|
@@ -1345,17 +1555,40 @@
|
|
1345 |
},
|
1346 |
{
|
1347 |
"case_id": "ioi",
|
|
|
|
|
|
|
|
|
1348 |
"files": [
|
1349 |
-
|
1350 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
1351 |
]
|
1352 |
},
|
1353 |
{
|
1354 |
"case_id": "ioi_next_token",
|
|
|
|
|
|
|
|
|
1355 |
"files": [
|
1356 |
-
|
1357 |
-
|
1358 |
-
|
|
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|
|
|
|
|
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|
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|
1359 |
]
|
1360 |
}
|
1361 |
]
|
|
|
2 |
"name": "InterpBench",
|
3 |
"version": "1.0.0",
|
4 |
"description": "A benchmark of transformers with known circuits for evaluating mechanistic interpretability techniques.",
|
5 |
+
"license": "https://creativecommons.org/licenses/by/4.0/",
|
6 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench",
|
7 |
"cases": [
|
8 |
{
|
9 |
"case_id": "11",
|
10 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/11",
|
|
|
|
|
|
|
|
|
|
|
11 |
"task_description": "Counts the number of words in a sequence based on their length.",
|
12 |
"vocab": [
|
13 |
"J",
|
14 |
+
"LB",
|
15 |
+
"TPSI",
|
|
|
16 |
"V",
|
17 |
"b",
|
18 |
+
"no",
|
19 |
+
"oCLrZaW",
|
20 |
+
"poiVg"
|
21 |
],
|
22 |
"max_seq_len": 10,
|
23 |
"min_seq_len": 4,
|
24 |
+
"files": [
|
25 |
+
{
|
26 |
+
"file_name": "edges.pkl",
|
27 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/11/edges.pkl"
|
28 |
+
},
|
29 |
+
{
|
30 |
+
"file_name": "ll_model_510.pth",
|
31 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/11/ll_model_510.pth"
|
32 |
+
},
|
33 |
+
{
|
34 |
+
"file_name": "ll_model_cfg_510.pkl",
|
35 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/11/ll_model_cfg_510.pkl"
|
36 |
+
},
|
37 |
+
{
|
38 |
+
"file_name": "meta_510.json",
|
39 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/11/meta_510.json"
|
40 |
+
}
|
41 |
+
],
|
42 |
"transformer_cfg": {
|
43 |
"n_layers": 2,
|
44 |
"d_model": 12,
|
|
|
106 |
},
|
107 |
{
|
108 |
"case_id": "13",
|
109 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/13",
|
|
|
|
|
|
|
|
|
|
|
110 |
"task_description": "Analyzes the trend (increasing, decreasing, constant) of numeric tokens.",
|
111 |
"vocab": [
|
112 |
0,
|
|
|
115 |
],
|
116 |
"max_seq_len": 10,
|
117 |
"min_seq_len": 4,
|
118 |
+
"files": [
|
119 |
+
{
|
120 |
+
"file_name": "edges.pkl",
|
121 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/13/edges.pkl"
|
122 |
+
},
|
123 |
+
{
|
124 |
+
"file_name": "ll_model_510.pth",
|
125 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/13/ll_model_510.pth"
|
126 |
+
},
|
127 |
+
{
|
128 |
+
"file_name": "ll_model_cfg_510.pkl",
|
129 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/13/ll_model_cfg_510.pkl"
|
130 |
+
},
|
131 |
+
{
|
132 |
+
"file_name": "meta_510.json",
|
133 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/13/meta_510.json"
|
134 |
+
}
|
135 |
+
],
|
136 |
"transformer_cfg": {
|
137 |
"n_layers": 2,
|
138 |
"d_model": 20,
|
|
|
200 |
},
|
201 |
{
|
202 |
"case_id": "18",
|
203 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/18",
|
|
|
|
|
|
|
|
|
|
|
204 |
"task_description": "Classify each token based on its frequency as 'rare', 'common', or 'frequent'.",
|
205 |
"vocab": [
|
206 |
+
"a",
|
|
|
207 |
"b",
|
208 |
+
"c",
|
209 |
"d",
|
210 |
+
"e"
|
211 |
],
|
212 |
"max_seq_len": 10,
|
213 |
"min_seq_len": 4,
|
214 |
+
"files": [
|
215 |
+
{
|
216 |
+
"file_name": "edges.pkl",
|
217 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/18/edges.pkl"
|
218 |
+
},
|
219 |
+
{
|
220 |
+
"file_name": "ll_model_510.pth",
|
221 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/18/ll_model_510.pth"
|
222 |
+
},
|
223 |
+
{
|
224 |
+
"file_name": "ll_model_cfg_510.pkl",
|
225 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/18/ll_model_cfg_510.pkl"
|
226 |
+
},
|
227 |
+
{
|
228 |
+
"file_name": "meta_510.json",
|
229 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/18/meta_510.json"
|
230 |
+
}
|
231 |
+
],
|
232 |
"transformer_cfg": {
|
233 |
"n_layers": 2,
|
234 |
"d_model": 12,
|
|
|
296 |
},
|
297 |
{
|
298 |
"case_id": "19",
|
299 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/19",
|
|
|
|
|
|
|
|
|
|
|
300 |
"task_description": "Removes consecutive duplicate tokens from a sequence.",
|
301 |
"vocab": [
|
|
|
302 |
"a",
|
303 |
+
"b",
|
304 |
"c"
|
305 |
],
|
306 |
"max_seq_len": 15,
|
307 |
"min_seq_len": 4,
|
308 |
+
"files": [
|
309 |
+
{
|
310 |
+
"file_name": "edges.pkl",
|
311 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/19/edges.pkl"
|
312 |
+
},
|
313 |
+
{
|
314 |
+
"file_name": "ll_model_510.pth",
|
315 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/19/ll_model_510.pth"
|
316 |
+
},
|
317 |
+
{
|
318 |
+
"file_name": "ll_model_cfg_510.pkl",
|
319 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/19/ll_model_cfg_510.pkl"
|
320 |
+
},
|
321 |
+
{
|
322 |
+
"file_name": "meta_510.json",
|
323 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/19/meta_510.json"
|
324 |
+
}
|
325 |
+
],
|
326 |
"transformer_cfg": {
|
327 |
"n_layers": 2,
|
328 |
"d_model": 32,
|
|
|
390 |
},
|
391 |
{
|
392 |
"case_id": "20",
|
393 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/20",
|
|
|
|
|
|
|
|
|
|
|
394 |
"task_description": "Detect spam messages based on appearance of spam keywords.",
|
395 |
"vocab": [
|
396 |
"J",
|
397 |
+
"LB",
|
398 |
+
"TPSI",
|
|
|
|
|
|
|
|
|
399 |
"V",
|
400 |
"b",
|
401 |
+
"click",
|
402 |
+
"no",
|
403 |
"now",
|
404 |
+
"oCLrZaW",
|
405 |
+
"offer",
|
406 |
+
"poiVg",
|
407 |
+
"spam"
|
408 |
],
|
409 |
"max_seq_len": 10,
|
410 |
"min_seq_len": 4,
|
411 |
+
"files": [
|
412 |
+
{
|
413 |
+
"file_name": "edges.pkl",
|
414 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/20/edges.pkl"
|
415 |
+
},
|
416 |
+
{
|
417 |
+
"file_name": "ll_model_1110.pth",
|
418 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/20/ll_model_1110.pth"
|
419 |
+
},
|
420 |
+
{
|
421 |
+
"file_name": "ll_model_cfg_1110.pkl",
|
422 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/20/ll_model_cfg_1110.pkl"
|
423 |
+
},
|
424 |
+
{
|
425 |
+
"file_name": "meta_1110.json",
|
426 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/20/meta_1110.json"
|
427 |
+
}
|
428 |
+
],
|
429 |
"transformer_cfg": {
|
430 |
"n_layers": 2,
|
431 |
"d_model": 4,
|
|
|
493 |
},
|
494 |
{
|
495 |
"case_id": "21",
|
496 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/21",
|
|
|
|
|
|
|
|
|
|
|
497 |
"task_description": "Extract unique tokens from a string",
|
498 |
"vocab": [
|
|
|
499 |
"a",
|
500 |
+
"b",
|
501 |
"c"
|
502 |
],
|
503 |
"max_seq_len": 10,
|
504 |
"min_seq_len": 4,
|
505 |
+
"files": [
|
506 |
+
{
|
507 |
+
"file_name": "edges.pkl",
|
508 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/21/edges.pkl"
|
509 |
+
},
|
510 |
+
{
|
511 |
+
"file_name": "ll_model_510.pth",
|
512 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/21/ll_model_510.pth"
|
513 |
+
},
|
514 |
+
{
|
515 |
+
"file_name": "ll_model_cfg_510.pkl",
|
516 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/21/ll_model_cfg_510.pkl"
|
517 |
+
},
|
518 |
+
{
|
519 |
+
"file_name": "meta_510.json",
|
520 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/21/meta_510.json"
|
521 |
+
}
|
522 |
+
],
|
523 |
"transformer_cfg": {
|
524 |
"n_layers": 2,
|
525 |
"d_model": 20,
|
|
|
587 |
},
|
588 |
{
|
589 |
"case_id": "24",
|
590 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/24",
|
|
|
|
|
|
|
|
|
|
|
591 |
"task_description": "Identifies the first occurrence of each token in a sequence.",
|
592 |
"vocab": [
|
|
|
593 |
"a",
|
594 |
+
"b",
|
595 |
"c"
|
596 |
],
|
597 |
"max_seq_len": 10,
|
598 |
"min_seq_len": 4,
|
599 |
+
"files": [
|
600 |
+
{
|
601 |
+
"file_name": "edges.pkl",
|
602 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/24/edges.pkl"
|
603 |
+
},
|
604 |
+
{
|
605 |
+
"file_name": "ll_model_510.pth",
|
606 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/24/ll_model_510.pth"
|
607 |
+
},
|
608 |
+
{
|
609 |
+
"file_name": "ll_model_cfg_510.pkl",
|
610 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/24/ll_model_cfg_510.pkl"
|
611 |
+
},
|
612 |
+
{
|
613 |
+
"file_name": "meta_510.json",
|
614 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/24/meta_510.json"
|
615 |
+
}
|
616 |
+
],
|
617 |
"transformer_cfg": {
|
618 |
"n_layers": 2,
|
619 |
"d_model": 20,
|
|
|
681 |
},
|
682 |
{
|
683 |
"case_id": "3",
|
684 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/3",
|
|
|
|
|
|
|
|
|
|
|
685 |
"task_description": "Returns the fraction of 'x' in the input up to the i-th position for all i.",
|
686 |
"vocab": [
|
|
|
|
|
687 |
"a",
|
688 |
+
"b",
|
689 |
+
"c",
|
690 |
+
"x"
|
691 |
],
|
692 |
"max_seq_len": 5,
|
693 |
"min_seq_len": 4,
|
694 |
+
"files": [
|
695 |
+
{
|
696 |
+
"file_name": "edges.pkl",
|
697 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/3/edges.pkl"
|
698 |
+
},
|
699 |
+
{
|
700 |
+
"file_name": "ll_model_10110.pth",
|
701 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/3/ll_model_10110.pth"
|
702 |
+
},
|
703 |
+
{
|
704 |
+
"file_name": "ll_model_cfg_10110.pkl",
|
705 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/3/ll_model_cfg_10110.pkl"
|
706 |
+
},
|
707 |
+
{
|
708 |
+
"file_name": "meta_10110.json",
|
709 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/3/meta_10110.json"
|
710 |
+
}
|
711 |
+
],
|
712 |
"transformer_cfg": {
|
713 |
"n_layers": 2,
|
714 |
"d_model": 12,
|
|
|
776 |
},
|
777 |
{
|
778 |
"case_id": "33",
|
779 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/33",
|
|
|
|
|
|
|
|
|
|
|
780 |
"task_description": "Checks if each token's length is odd or even.",
|
781 |
"vocab": [
|
782 |
"J",
|
783 |
+
"LB",
|
784 |
+
"TPSI",
|
|
|
785 |
"V",
|
786 |
"b",
|
787 |
+
"no",
|
788 |
+
"oCLrZaW",
|
789 |
+
"poiVg"
|
790 |
],
|
791 |
"max_seq_len": 10,
|
792 |
"min_seq_len": 4,
|
793 |
+
"files": [
|
794 |
+
{
|
795 |
+
"file_name": "edges.pkl",
|
796 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/33/edges.pkl"
|
797 |
+
},
|
798 |
+
{
|
799 |
+
"file_name": "ll_model_510.pth",
|
800 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/33/ll_model_510.pth"
|
801 |
+
},
|
802 |
+
{
|
803 |
+
"file_name": "ll_model_cfg_510.pkl",
|
804 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/33/ll_model_cfg_510.pkl"
|
805 |
+
},
|
806 |
+
{
|
807 |
+
"file_name": "meta_510.json",
|
808 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/33/meta_510.json"
|
809 |
+
}
|
810 |
+
],
|
811 |
"transformer_cfg": {
|
812 |
"n_layers": 2,
|
813 |
"d_model": 4,
|
|
|
875 |
},
|
876 |
{
|
877 |
"case_id": "34",
|
878 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/34",
|
|
|
|
|
|
|
|
|
|
|
879 |
"task_description": "Calculate the ratio of vowels to consonants in each word.",
|
880 |
"vocab": [
|
881 |
"J",
|
882 |
+
"LB",
|
883 |
+
"TPSI",
|
|
|
884 |
"V",
|
885 |
"b",
|
886 |
+
"no",
|
887 |
+
"oCLrZaW",
|
888 |
+
"poiVg"
|
889 |
],
|
890 |
"max_seq_len": 10,
|
891 |
"min_seq_len": 4,
|
892 |
+
"files": [
|
893 |
+
{
|
894 |
+
"file_name": "edges.pkl",
|
895 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/34/edges.pkl"
|
896 |
+
},
|
897 |
+
{
|
898 |
+
"file_name": "ll_model_510.pth",
|
899 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/34/ll_model_510.pth"
|
900 |
+
},
|
901 |
+
{
|
902 |
+
"file_name": "ll_model_cfg_510.pkl",
|
903 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/34/ll_model_cfg_510.pkl"
|
904 |
+
},
|
905 |
+
{
|
906 |
+
"file_name": "meta_510.json",
|
907 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/34/meta_510.json"
|
908 |
+
}
|
909 |
+
],
|
910 |
"transformer_cfg": {
|
911 |
"n_layers": 2,
|
912 |
"d_model": 4,
|
|
|
974 |
},
|
975 |
{
|
976 |
"case_id": "35",
|
977 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/35",
|
|
|
|
|
|
|
|
|
|
|
978 |
"task_description": "Alternates capitalization of each character in words.",
|
979 |
"vocab": [
|
980 |
"J",
|
981 |
+
"LB",
|
982 |
+
"TPSI",
|
|
|
983 |
"V",
|
984 |
"b",
|
985 |
+
"no",
|
986 |
+
"oCLrZaW",
|
987 |
+
"poiVg"
|
988 |
],
|
989 |
"max_seq_len": 10,
|
990 |
"min_seq_len": 4,
|
991 |
+
"files": [
|
992 |
+
{
|
993 |
+
"file_name": "edges.pkl",
|
994 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/35/edges.pkl"
|
995 |
+
},
|
996 |
+
{
|
997 |
+
"file_name": "ll_model_510.pth",
|
998 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/35/ll_model_510.pth"
|
999 |
+
},
|
1000 |
+
{
|
1001 |
+
"file_name": "ll_model_cfg_510.pkl",
|
1002 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/35/ll_model_cfg_510.pkl"
|
1003 |
+
},
|
1004 |
+
{
|
1005 |
+
"file_name": "meta_510.json",
|
1006 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/35/meta_510.json"
|
1007 |
+
}
|
1008 |
+
],
|
1009 |
"transformer_cfg": {
|
1010 |
"n_layers": 2,
|
1011 |
"d_model": 4,
|
|
|
1073 |
},
|
1074 |
{
|
1075 |
"case_id": "36",
|
1076 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/36",
|
|
|
|
|
|
|
|
|
|
|
1077 |
"task_description": "Classifies each token as 'positive', 'negative', or 'neutral' based on emojis.",
|
1078 |
"vocab": [
|
|
|
1079 |
"\ud83d\udcd8",
|
1080 |
+
"\ud83d\ude0a",
|
1081 |
+
"\ud83d\ude22"
|
1082 |
],
|
1083 |
"max_seq_len": 10,
|
1084 |
"min_seq_len": 4,
|
1085 |
+
"files": [
|
1086 |
+
{
|
1087 |
+
"file_name": "edges.pkl",
|
1088 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/36/edges.pkl"
|
1089 |
+
},
|
1090 |
+
{
|
1091 |
+
"file_name": "ll_model_10110.pth",
|
1092 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/36/ll_model_10110.pth"
|
1093 |
+
},
|
1094 |
+
{
|
1095 |
+
"file_name": "ll_model_cfg_10110.pkl",
|
1096 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/36/ll_model_cfg_10110.pkl"
|
1097 |
+
},
|
1098 |
+
{
|
1099 |
+
"file_name": "meta_10110.json",
|
1100 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/36/meta_10110.json"
|
1101 |
+
}
|
1102 |
+
],
|
1103 |
"transformer_cfg": {
|
1104 |
"n_layers": 2,
|
1105 |
"d_model": 4,
|
|
|
1167 |
},
|
1168 |
{
|
1169 |
"case_id": "37",
|
1170 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/37",
|
|
|
|
|
|
|
|
|
|
|
1171 |
"task_description": "Reverses each word in the sequence except for specified exclusions.",
|
1172 |
"vocab": [
|
1173 |
"J",
|
1174 |
+
"LB",
|
1175 |
+
"TPSI",
|
|
|
1176 |
"V",
|
1177 |
"b",
|
1178 |
+
"no",
|
1179 |
+
"oCLrZaW",
|
1180 |
+
"poiVg"
|
1181 |
],
|
1182 |
"max_seq_len": 10,
|
1183 |
"min_seq_len": 4,
|
1184 |
+
"files": [
|
1185 |
+
{
|
1186 |
+
"file_name": "edges.pkl",
|
1187 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/37/edges.pkl"
|
1188 |
+
},
|
1189 |
+
{
|
1190 |
+
"file_name": "ll_model_510.pth",
|
1191 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/37/ll_model_510.pth"
|
1192 |
+
},
|
1193 |
+
{
|
1194 |
+
"file_name": "ll_model_cfg_510.pkl",
|
1195 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/37/ll_model_cfg_510.pkl"
|
1196 |
+
},
|
1197 |
+
{
|
1198 |
+
"file_name": "meta_510.json",
|
1199 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/37/meta_510.json"
|
1200 |
+
}
|
1201 |
+
],
|
1202 |
"transformer_cfg": {
|
1203 |
"n_layers": 2,
|
1204 |
"d_model": 4,
|
|
|
1266 |
},
|
1267 |
{
|
1268 |
"case_id": "38",
|
1269 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/38",
|
|
|
|
|
|
|
|
|
|
|
1270 |
"task_description": "Checks if tokens alternate between two types.",
|
1271 |
"vocab": [
|
|
|
1272 |
"a",
|
1273 |
+
"b",
|
1274 |
"c"
|
1275 |
],
|
1276 |
"max_seq_len": 10,
|
1277 |
"min_seq_len": 4,
|
1278 |
+
"files": [
|
1279 |
+
{
|
1280 |
+
"file_name": "edges.pkl",
|
1281 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/38/edges.pkl"
|
1282 |
+
},
|
1283 |
+
{
|
1284 |
+
"file_name": "ll_model_510.pth",
|
1285 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/38/ll_model_510.pth"
|
1286 |
+
},
|
1287 |
+
{
|
1288 |
+
"file_name": "ll_model_cfg_510.pkl",
|
1289 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/38/ll_model_cfg_510.pkl"
|
1290 |
+
},
|
1291 |
+
{
|
1292 |
+
"file_name": "meta_510.json",
|
1293 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/38/meta_510.json"
|
1294 |
+
}
|
1295 |
+
],
|
1296 |
"transformer_cfg": {
|
1297 |
"n_layers": 2,
|
1298 |
"d_model": 20,
|
|
|
1360 |
},
|
1361 |
{
|
1362 |
"case_id": "4",
|
1363 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/4",
|
|
|
|
|
|
|
|
|
|
|
1364 |
"task_description": "Return fraction of previous open tokens minus the fraction of close tokens.",
|
1365 |
"vocab": [
|
|
|
1366 |
"(",
|
|
|
1367 |
")",
|
1368 |
+
"a",
|
1369 |
+
"b",
|
1370 |
+
"c"
|
1371 |
],
|
1372 |
"max_seq_len": 10,
|
1373 |
"min_seq_len": 4,
|
1374 |
+
"files": [
|
1375 |
+
{
|
1376 |
+
"file_name": "edges.pkl",
|
1377 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/4/edges.pkl"
|
1378 |
+
},
|
1379 |
+
{
|
1380 |
+
"file_name": "ll_model_510.pth",
|
1381 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/4/ll_model_510.pth"
|
1382 |
+
},
|
1383 |
+
{
|
1384 |
+
"file_name": "ll_model_cfg_510.pkl",
|
1385 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/4/ll_model_cfg_510.pkl"
|
1386 |
+
},
|
1387 |
+
{
|
1388 |
+
"file_name": "meta_510.json",
|
1389 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/4/meta_510.json"
|
1390 |
+
}
|
1391 |
+
],
|
1392 |
"transformer_cfg": {
|
1393 |
"n_layers": 2,
|
1394 |
"d_model": 20,
|
|
|
1456 |
},
|
1457 |
{
|
1458 |
"case_id": "8",
|
1459 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/8",
|
|
|
|
|
|
|
|
|
|
|
1460 |
"task_description": "Fills gaps between tokens with a specified filler.",
|
1461 |
"vocab": [
|
1462 |
"J",
|
1463 |
+
"LB",
|
1464 |
+
"TPSI",
|
|
|
1465 |
"V",
|
1466 |
"b",
|
1467 |
+
"no",
|
1468 |
+
"oCLrZaW",
|
1469 |
+
"poiVg"
|
1470 |
],
|
1471 |
"max_seq_len": 10,
|
1472 |
"min_seq_len": 4,
|
1473 |
+
"files": [
|
1474 |
+
{
|
1475 |
+
"file_name": "edges.pkl",
|
1476 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/8/edges.pkl"
|
1477 |
+
},
|
1478 |
+
{
|
1479 |
+
"file_name": "ll_model_510.pth",
|
1480 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/8/ll_model_510.pth"
|
1481 |
+
},
|
1482 |
+
{
|
1483 |
+
"file_name": "ll_model_cfg_510.pkl",
|
1484 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/8/ll_model_cfg_510.pkl"
|
1485 |
+
},
|
1486 |
+
{
|
1487 |
+
"file_name": "meta_510.json",
|
1488 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/8/meta_510.json"
|
1489 |
+
}
|
1490 |
+
],
|
1491 |
"transformer_cfg": {
|
1492 |
"n_layers": 2,
|
1493 |
"d_model": 20,
|
|
|
1555 |
},
|
1556 |
{
|
1557 |
"case_id": "ioi",
|
1558 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/ioi",
|
1559 |
+
"task_description": "Indirect object identification",
|
1560 |
+
"max_seq_len": 16,
|
1561 |
+
"min_seq_len": 16,
|
1562 |
"files": [
|
1563 |
+
{
|
1564 |
+
"file_name": "corr_100_100_40.json",
|
1565 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/ioi/corr_100_100_40.json"
|
1566 |
+
},
|
1567 |
+
{
|
1568 |
+
"file_name": "ll_model_100_100_40.pth",
|
1569 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/ioi/ll_model_100_100_40.pth"
|
1570 |
+
}
|
1571 |
]
|
1572 |
},
|
1573 |
{
|
1574 |
"case_id": "ioi_next_token",
|
1575 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/tree/main/ioi_next_token",
|
1576 |
+
"task_description": "Indirect object identification",
|
1577 |
+
"max_seq_len": 16,
|
1578 |
+
"min_seq_len": 16,
|
1579 |
"files": [
|
1580 |
+
{
|
1581 |
+
"file_name": "corr_100_100_40.json",
|
1582 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/ioi_next_token/corr_100_100_40.json"
|
1583 |
+
},
|
1584 |
+
{
|
1585 |
+
"file_name": "ll_model_100_100_40.pth",
|
1586 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/ioi_next_token/ll_model_100_100_40.pth"
|
1587 |
+
},
|
1588 |
+
{
|
1589 |
+
"file_name": "training_args.json",
|
1590 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench/blob/main/ioi_next_token/training_args.json"
|
1591 |
+
}
|
1592 |
]
|
1593 |
}
|
1594 |
]
|
benchmark_metadata_croissant.json
ADDED
@@ -0,0 +1,1103 @@
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|
|
|
1 |
+
{
|
2 |
+
"@context": {
|
3 |
+
"@language": "en",
|
4 |
+
"@vocab": "https://schema.org/",
|
5 |
+
"citeAs": "cr:citeAs",
|
6 |
+
"column": "cr:column",
|
7 |
+
"conformsTo": "dct:conformsTo",
|
8 |
+
"cr": "http://mlcommons.org/croissant/",
|
9 |
+
"rai": "http://mlcommons.org/croissant/RAI/",
|
10 |
+
"data": {
|
11 |
+
"@id": "cr:data",
|
12 |
+
"@type": "@json"
|
13 |
+
},
|
14 |
+
"dataType": {
|
15 |
+
"@id": "cr:dataType",
|
16 |
+
"@type": "@vocab"
|
17 |
+
},
|
18 |
+
"dct": "http://purl.org/dc/terms/",
|
19 |
+
"examples": {
|
20 |
+
"@id": "cr:examples",
|
21 |
+
"@type": "@json"
|
22 |
+
},
|
23 |
+
"extract": "cr:extract",
|
24 |
+
"field": "cr:field",
|
25 |
+
"fileProperty": "cr:fileProperty",
|
26 |
+
"fileObject": "cr:fileObject",
|
27 |
+
"fileSet": "cr:fileSet",
|
28 |
+
"format": "cr:format",
|
29 |
+
"includes": "cr:includes",
|
30 |
+
"isLiveDataset": "cr:isLiveDataset",
|
31 |
+
"jsonPath": "cr:jsonPath",
|
32 |
+
"key": "cr:key",
|
33 |
+
"md5": "cr:md5",
|
34 |
+
"parentField": "cr:parentField",
|
35 |
+
"path": "cr:path",
|
36 |
+
"recordSet": "cr:recordSet",
|
37 |
+
"references": "cr:references",
|
38 |
+
"regex": "cr:regex",
|
39 |
+
"repeated": "cr:repeated",
|
40 |
+
"replace": "cr:replace",
|
41 |
+
"sc": "https://schema.org/",
|
42 |
+
"separator": "cr:separator",
|
43 |
+
"source": "cr:source",
|
44 |
+
"subField": "cr:subField",
|
45 |
+
"transform": "cr:transform"
|
46 |
+
},
|
47 |
+
"@type": "sc:Dataset",
|
48 |
+
"name": "InterpBench",
|
49 |
+
"description": "A benchmark of transformers with known circuits for evaluating mechanistic interpretability techniques.",
|
50 |
+
"conformsTo": "http://mlcommons.org/croissant/1.0",
|
51 |
+
"license": "https://creativecommons.org/licenses/by/4.0/",
|
52 |
+
"url": "https://huggingface.co/cybershiptrooper/InterpBench",
|
53 |
+
"version": "1.0.0",
|
54 |
+
"distribution": [
|
55 |
+
{
|
56 |
+
"@type": "cr:FileObject",
|
57 |
+
"@id": "hf-repository",
|
58 |
+
"name": "hf-repository",
|
59 |
+
"description": "The Hugging Face git repository.",
|
60 |
+
"contentUrl": "https://huggingface.co/cybershiptrooper/InterpBench",
|
61 |
+
"encodingFormat": "git+https",
|
62 |
+
"sha256": "main"
|
63 |
+
},
|
64 |
+
{
|
65 |
+
"@type": "cr:FileObject",
|
66 |
+
"@id": "benchmark-cases-parquet",
|
67 |
+
"name": "benchmark-cases-parquet",
|
68 |
+
"description": "Parquet file describing all the cases in the benchmark.",
|
69 |
+
"containedIn": {
|
70 |
+
"@id": "hf-repository"
|
71 |
+
},
|
72 |
+
"encodingFormat": "application/x-parquet"
|
73 |
+
},
|
74 |
+
{
|
75 |
+
"@type": "cr:FileSet",
|
76 |
+
"@id": "training-args",
|
77 |
+
"name": "training-args",
|
78 |
+
"description": "Training arguments.",
|
79 |
+
"containedIn": {
|
80 |
+
"@id": "hf-repository"
|
81 |
+
},
|
82 |
+
"encodingFormat": "application/json",
|
83 |
+
"includes": "*/meta_[0-9]*.json"
|
84 |
+
},
|
85 |
+
{
|
86 |
+
"@type": "cr:FileSet",
|
87 |
+
"@id": "circuits",
|
88 |
+
"name": "circuits",
|
89 |
+
"description": "Ground truth circuits (Pickle).",
|
90 |
+
"containedIn": {
|
91 |
+
"@id": "hf-repository"
|
92 |
+
},
|
93 |
+
"encodingFormat": "application/octet-stream",
|
94 |
+
"includes": "*/edges.pkl"
|
95 |
+
},
|
96 |
+
{
|
97 |
+
"@type": "cr:FileSet",
|
98 |
+
"@id": "weights",
|
99 |
+
"name": "weights",
|
100 |
+
"description": "Serialized PyTorch state dictionaries (Pickle).",
|
101 |
+
"containedIn": {
|
102 |
+
"@id": "hf-repository"
|
103 |
+
},
|
104 |
+
"encodingFormat": "application/octet-stream",
|
105 |
+
"includes": "*/ll_model_[0-9]*.pkl"
|
106 |
+
},
|
107 |
+
{
|
108 |
+
"@type": "cr:FileSet",
|
109 |
+
"@id": "cfgs",
|
110 |
+
"name": "cfgs",
|
111 |
+
"description": "Architecture configs (Pickle).",
|
112 |
+
"containedIn": {
|
113 |
+
"@id": "hf-repository"
|
114 |
+
},
|
115 |
+
"encodingFormat": "application/octet-stream",
|
116 |
+
"includes": "*/ll_model_cfg_[0-9]*.pkl"
|
117 |
+
}
|
118 |
+
],
|
119 |
+
"recordSet": [
|
120 |
+
{
|
121 |
+
"@type": "cr:RecordSet",
|
122 |
+
"@id": "cases",
|
123 |
+
"name": "cases",
|
124 |
+
"field": [
|
125 |
+
{
|
126 |
+
"@type": "cr:Field",
|
127 |
+
"@id": "case_id",
|
128 |
+
"name": "case_id",
|
129 |
+
"description": "Column 'case_id' from the parquet file describing all the cases in the benchmark.",
|
130 |
+
"dataType": "sc:Text",
|
131 |
+
"source": {
|
132 |
+
"fileSet": {
|
133 |
+
"@id": "benchmark-cases-parquet"
|
134 |
+
},
|
135 |
+
"extract": {
|
136 |
+
"column": "case_id"
|
137 |
+
}
|
138 |
+
}
|
139 |
+
},
|
140 |
+
{
|
141 |
+
"@type": "cr:Field",
|
142 |
+
"@id": "url",
|
143 |
+
"name": "url",
|
144 |
+
"description": "Column 'url' from the parquet file describing all the cases in the benchmark.",
|
145 |
+
"dataType": "sc:Text",
|
146 |
+
"source": {
|
147 |
+
"fileSet": {
|
148 |
+
"@id": "benchmark-cases-parquet"
|
149 |
+
},
|
150 |
+
"extract": {
|
151 |
+
"column": "url"
|
152 |
+
}
|
153 |
+
}
|
154 |
+
},
|
155 |
+
{
|
156 |
+
"@type": "cr:Field",
|
157 |
+
"@id": "task_description",
|
158 |
+
"name": "task_description",
|
159 |
+
"description": "Column 'task_description' from the parquet file describing all the cases in the benchmark.",
|
160 |
+
"dataType": "sc:Text",
|
161 |
+
"source": {
|
162 |
+
"fileSet": {
|
163 |
+
"@id": "benchmark-cases-parquet"
|
164 |
+
},
|
165 |
+
"extract": {
|
166 |
+
"column": "task_description"
|
167 |
+
}
|
168 |
+
}
|
169 |
+
},
|
170 |
+
{
|
171 |
+
"@type": "cr:Field",
|
172 |
+
"@id": "max_seq_len",
|
173 |
+
"name": "max_seq_len",
|
174 |
+
"description": "Column 'max_seq_len' from the parquet file describing all the cases in the benchmark.",
|
175 |
+
"dataType": "sc:Integer",
|
176 |
+
"source": {
|
177 |
+
"fileSet": {
|
178 |
+
"@id": "benchmark-cases-parquet"
|
179 |
+
},
|
180 |
+
"extract": {
|
181 |
+
"column": "max_seq_len"
|
182 |
+
}
|
183 |
+
}
|
184 |
+
},
|
185 |
+
{
|
186 |
+
"@type": "cr:Field",
|
187 |
+
"@id": "min_seq_len",
|
188 |
+
"name": "min_seq_len",
|
189 |
+
"description": "Column 'min_seq_len' from the parquet file describing all the cases in the benchmark.",
|
190 |
+
"dataType": "sc:Integer",
|
191 |
+
"source": {
|
192 |
+
"fileSet": {
|
193 |
+
"@id": "benchmark-cases-parquet"
|
194 |
+
},
|
195 |
+
"extract": {
|
196 |
+
"column": "min_seq_len"
|
197 |
+
}
|
198 |
+
}
|
199 |
+
},
|
200 |
+
{
|
201 |
+
"@type": "cr:Field",
|
202 |
+
"@id": "training_args.atol",
|
203 |
+
"name": "training_args.atol",
|
204 |
+
"description": "Column 'training_args.atol' from the parquet file describing all the cases in the benchmark.",
|
205 |
+
"dataType": "sc:Float",
|
206 |
+
"source": {
|
207 |
+
"fileSet": {
|
208 |
+
"@id": "benchmark-cases-parquet"
|
209 |
+
},
|
210 |
+
"extract": {
|
211 |
+
"column": "training_args.atol"
|
212 |
+
}
|
213 |
+
}
|
214 |
+
},
|
215 |
+
{
|
216 |
+
"@type": "cr:Field",
|
217 |
+
"@id": "training_args.lr",
|
218 |
+
"name": "training_args.lr",
|
219 |
+
"description": "Column 'training_args.lr' from the parquet file describing all the cases in the benchmark.",
|
220 |
+
"dataType": "sc:Float",
|
221 |
+
"source": {
|
222 |
+
"fileSet": {
|
223 |
+
"@id": "benchmark-cases-parquet"
|
224 |
+
},
|
225 |
+
"extract": {
|
226 |
+
"column": "training_args.lr"
|
227 |
+
}
|
228 |
+
}
|
229 |
+
},
|
230 |
+
{
|
231 |
+
"@type": "cr:Field",
|
232 |
+
"@id": "training_args.use_single_loss",
|
233 |
+
"name": "training_args.use_single_loss",
|
234 |
+
"description": "Column 'training_args.use_single_loss' from the parquet file describing all the cases in the benchmark.",
|
235 |
+
"dataType": "sc:Boolean",
|
236 |
+
"source": {
|
237 |
+
"fileSet": {
|
238 |
+
"@id": "benchmark-cases-parquet"
|
239 |
+
},
|
240 |
+
"extract": {
|
241 |
+
"column": "training_args.use_single_loss"
|
242 |
+
}
|
243 |
+
}
|
244 |
+
},
|
245 |
+
{
|
246 |
+
"@type": "cr:Field",
|
247 |
+
"@id": "training_args.iit_weight",
|
248 |
+
"name": "training_args.iit_weight",
|
249 |
+
"description": "Column 'training_args.iit_weight' from the parquet file describing all the cases in the benchmark.",
|
250 |
+
"dataType": "sc:Float",
|
251 |
+
"source": {
|
252 |
+
"fileSet": {
|
253 |
+
"@id": "benchmark-cases-parquet"
|
254 |
+
},
|
255 |
+
"extract": {
|
256 |
+
"column": "training_args.iit_weight"
|
257 |
+
}
|
258 |
+
}
|
259 |
+
},
|
260 |
+
{
|
261 |
+
"@type": "cr:Field",
|
262 |
+
"@id": "training_args.behavior_weight",
|
263 |
+
"name": "training_args.behavior_weight",
|
264 |
+
"description": "Column 'training_args.behavior_weight' from the parquet file describing all the cases in the benchmark.",
|
265 |
+
"dataType": "sc:Float",
|
266 |
+
"source": {
|
267 |
+
"fileSet": {
|
268 |
+
"@id": "benchmark-cases-parquet"
|
269 |
+
},
|
270 |
+
"extract": {
|
271 |
+
"column": "training_args.behavior_weight"
|
272 |
+
}
|
273 |
+
}
|
274 |
+
},
|
275 |
+
{
|
276 |
+
"@type": "cr:Field",
|
277 |
+
"@id": "training_args.strict_weight",
|
278 |
+
"name": "training_args.strict_weight",
|
279 |
+
"description": "Column 'training_args.strict_weight' from the parquet file describing all the cases in the benchmark.",
|
280 |
+
"dataType": "sc:Float",
|
281 |
+
"source": {
|
282 |
+
"fileSet": {
|
283 |
+
"@id": "benchmark-cases-parquet"
|
284 |
+
},
|
285 |
+
"extract": {
|
286 |
+
"column": "training_args.strict_weight"
|
287 |
+
}
|
288 |
+
}
|
289 |
+
},
|
290 |
+
{
|
291 |
+
"@type": "cr:Field",
|
292 |
+
"@id": "training_args.epochs",
|
293 |
+
"name": "training_args.epochs",
|
294 |
+
"description": "Column 'training_args.epochs' from the parquet file describing all the cases in the benchmark.",
|
295 |
+
"dataType": "sc:Float",
|
296 |
+
"source": {
|
297 |
+
"fileSet": {
|
298 |
+
"@id": "benchmark-cases-parquet"
|
299 |
+
},
|
300 |
+
"extract": {
|
301 |
+
"column": "training_args.epochs"
|
302 |
+
}
|
303 |
+
}
|
304 |
+
},
|
305 |
+
{
|
306 |
+
"@type": "cr:Field",
|
307 |
+
"@id": "training_args.act_fn",
|
308 |
+
"name": "training_args.act_fn",
|
309 |
+
"description": "Column 'training_args.act_fn' from the parquet file describing all the cases in the benchmark.",
|
310 |
+
"dataType": "sc:Text",
|
311 |
+
"source": {
|
312 |
+
"fileSet": {
|
313 |
+
"@id": "benchmark-cases-parquet"
|
314 |
+
},
|
315 |
+
"extract": {
|
316 |
+
"column": "training_args.act_fn"
|
317 |
+
}
|
318 |
+
}
|
319 |
+
},
|
320 |
+
{
|
321 |
+
"@type": "cr:Field",
|
322 |
+
"@id": "training_args.clip_grad_norm",
|
323 |
+
"name": "training_args.clip_grad_norm",
|
324 |
+
"description": "Column 'training_args.clip_grad_norm' from the parquet file describing all the cases in the benchmark.",
|
325 |
+
"dataType": "sc:Float",
|
326 |
+
"source": {
|
327 |
+
"fileSet": {
|
328 |
+
"@id": "benchmark-cases-parquet"
|
329 |
+
},
|
330 |
+
"extract": {
|
331 |
+
"column": "training_args.clip_grad_norm"
|
332 |
+
}
|
333 |
+
}
|
334 |
+
},
|
335 |
+
{
|
336 |
+
"@type": "cr:Field",
|
337 |
+
"@id": "training_args.lr_scheduler",
|
338 |
+
"name": "training_args.lr_scheduler",
|
339 |
+
"description": "Column 'training_args.lr_scheduler' from the parquet file describing all the cases in the benchmark.",
|
340 |
+
"dataType": "sc:Text",
|
341 |
+
"source": {
|
342 |
+
"fileSet": {
|
343 |
+
"@id": "benchmark-cases-parquet"
|
344 |
+
},
|
345 |
+
"extract": {
|
346 |
+
"column": "training_args.lr_scheduler"
|
347 |
+
}
|
348 |
+
}
|
349 |
+
},
|
350 |
+
{
|
351 |
+
"@type": "cr:Field",
|
352 |
+
"@id": "transformer_cfg.n_layers",
|
353 |
+
"name": "transformer_cfg.n_layers",
|
354 |
+
"description": "Column 'transformer_cfg.n_layers' from the parquet file describing all the cases in the benchmark.",
|
355 |
+
"dataType": "sc:Float",
|
356 |
+
"source": {
|
357 |
+
"fileSet": {
|
358 |
+
"@id": "benchmark-cases-parquet"
|
359 |
+
},
|
360 |
+
"extract": {
|
361 |
+
"column": "transformer_cfg.n_layers"
|
362 |
+
}
|
363 |
+
}
|
364 |
+
},
|
365 |
+
{
|
366 |
+
"@type": "cr:Field",
|
367 |
+
"@id": "transformer_cfg.d_model",
|
368 |
+
"name": "transformer_cfg.d_model",
|
369 |
+
"description": "Column 'transformer_cfg.d_model' from the parquet file describing all the cases in the benchmark.",
|
370 |
+
"dataType": "sc:Float",
|
371 |
+
"source": {
|
372 |
+
"fileSet": {
|
373 |
+
"@id": "benchmark-cases-parquet"
|
374 |
+
},
|
375 |
+
"extract": {
|
376 |
+
"column": "transformer_cfg.d_model"
|
377 |
+
}
|
378 |
+
}
|
379 |
+
},
|
380 |
+
{
|
381 |
+
"@type": "cr:Field",
|
382 |
+
"@id": "transformer_cfg.n_ctx",
|
383 |
+
"name": "transformer_cfg.n_ctx",
|
384 |
+
"description": "Column 'transformer_cfg.n_ctx' from the parquet file describing all the cases in the benchmark.",
|
385 |
+
"dataType": "sc:Float",
|
386 |
+
"source": {
|
387 |
+
"fileSet": {
|
388 |
+
"@id": "benchmark-cases-parquet"
|
389 |
+
},
|
390 |
+
"extract": {
|
391 |
+
"column": "transformer_cfg.n_ctx"
|
392 |
+
}
|
393 |
+
}
|
394 |
+
},
|
395 |
+
{
|
396 |
+
"@type": "cr:Field",
|
397 |
+
"@id": "transformer_cfg.d_head",
|
398 |
+
"name": "transformer_cfg.d_head",
|
399 |
+
"description": "Column 'transformer_cfg.d_head' from the parquet file describing all the cases in the benchmark.",
|
400 |
+
"dataType": "sc:Float",
|
401 |
+
"source": {
|
402 |
+
"fileSet": {
|
403 |
+
"@id": "benchmark-cases-parquet"
|
404 |
+
},
|
405 |
+
"extract": {
|
406 |
+
"column": "transformer_cfg.d_head"
|
407 |
+
}
|
408 |
+
}
|
409 |
+
},
|
410 |
+
{
|
411 |
+
"@type": "cr:Field",
|
412 |
+
"@id": "transformer_cfg.model_name",
|
413 |
+
"name": "transformer_cfg.model_name",
|
414 |
+
"description": "Column 'transformer_cfg.model_name' from the parquet file describing all the cases in the benchmark.",
|
415 |
+
"dataType": "sc:Text",
|
416 |
+
"source": {
|
417 |
+
"fileSet": {
|
418 |
+
"@id": "benchmark-cases-parquet"
|
419 |
+
},
|
420 |
+
"extract": {
|
421 |
+
"column": "transformer_cfg.model_name"
|
422 |
+
}
|
423 |
+
}
|
424 |
+
},
|
425 |
+
{
|
426 |
+
"@type": "cr:Field",
|
427 |
+
"@id": "transformer_cfg.n_heads",
|
428 |
+
"name": "transformer_cfg.n_heads",
|
429 |
+
"description": "Column 'transformer_cfg.n_heads' from the parquet file describing all the cases in the benchmark.",
|
430 |
+
"dataType": "sc:Float",
|
431 |
+
"source": {
|
432 |
+
"fileSet": {
|
433 |
+
"@id": "benchmark-cases-parquet"
|
434 |
+
},
|
435 |
+
"extract": {
|
436 |
+
"column": "transformer_cfg.n_heads"
|
437 |
+
}
|
438 |
+
}
|
439 |
+
},
|
440 |
+
{
|
441 |
+
"@type": "cr:Field",
|
442 |
+
"@id": "transformer_cfg.d_mlp",
|
443 |
+
"name": "transformer_cfg.d_mlp",
|
444 |
+
"description": "Column 'transformer_cfg.d_mlp' from the parquet file describing all the cases in the benchmark.",
|
445 |
+
"dataType": "sc:Float",
|
446 |
+
"source": {
|
447 |
+
"fileSet": {
|
448 |
+
"@id": "benchmark-cases-parquet"
|
449 |
+
},
|
450 |
+
"extract": {
|
451 |
+
"column": "transformer_cfg.d_mlp"
|
452 |
+
}
|
453 |
+
}
|
454 |
+
},
|
455 |
+
{
|
456 |
+
"@type": "cr:Field",
|
457 |
+
"@id": "transformer_cfg.act_fn",
|
458 |
+
"name": "transformer_cfg.act_fn",
|
459 |
+
"description": "Column 'transformer_cfg.act_fn' from the parquet file describing all the cases in the benchmark.",
|
460 |
+
"dataType": "sc:Text",
|
461 |
+
"source": {
|
462 |
+
"fileSet": {
|
463 |
+
"@id": "benchmark-cases-parquet"
|
464 |
+
},
|
465 |
+
"extract": {
|
466 |
+
"column": "transformer_cfg.act_fn"
|
467 |
+
}
|
468 |
+
}
|
469 |
+
},
|
470 |
+
{
|
471 |
+
"@type": "cr:Field",
|
472 |
+
"@id": "transformer_cfg.d_vocab",
|
473 |
+
"name": "transformer_cfg.d_vocab",
|
474 |
+
"description": "Column 'transformer_cfg.d_vocab' from the parquet file describing all the cases in the benchmark.",
|
475 |
+
"dataType": "sc:Float",
|
476 |
+
"source": {
|
477 |
+
"fileSet": {
|
478 |
+
"@id": "benchmark-cases-parquet"
|
479 |
+
},
|
480 |
+
"extract": {
|
481 |
+
"column": "transformer_cfg.d_vocab"
|
482 |
+
}
|
483 |
+
}
|
484 |
+
},
|
485 |
+
{
|
486 |
+
"@type": "cr:Field",
|
487 |
+
"@id": "transformer_cfg.eps",
|
488 |
+
"name": "transformer_cfg.eps",
|
489 |
+
"description": "Column 'transformer_cfg.eps' from the parquet file describing all the cases in the benchmark.",
|
490 |
+
"dataType": "sc:Float",
|
491 |
+
"source": {
|
492 |
+
"fileSet": {
|
493 |
+
"@id": "benchmark-cases-parquet"
|
494 |
+
},
|
495 |
+
"extract": {
|
496 |
+
"column": "transformer_cfg.eps"
|
497 |
+
}
|
498 |
+
}
|
499 |
+
},
|
500 |
+
{
|
501 |
+
"@type": "cr:Field",
|
502 |
+
"@id": "transformer_cfg.use_attn_result",
|
503 |
+
"name": "transformer_cfg.use_attn_result",
|
504 |
+
"description": "Column 'transformer_cfg.use_attn_result' from the parquet file describing all the cases in the benchmark.",
|
505 |
+
"dataType": "sc:Boolean",
|
506 |
+
"source": {
|
507 |
+
"fileSet": {
|
508 |
+
"@id": "benchmark-cases-parquet"
|
509 |
+
},
|
510 |
+
"extract": {
|
511 |
+
"column": "transformer_cfg.use_attn_result"
|
512 |
+
}
|
513 |
+
}
|
514 |
+
},
|
515 |
+
{
|
516 |
+
"@type": "cr:Field",
|
517 |
+
"@id": "transformer_cfg.use_attn_scale",
|
518 |
+
"name": "transformer_cfg.use_attn_scale",
|
519 |
+
"description": "Column 'transformer_cfg.use_attn_scale' from the parquet file describing all the cases in the benchmark.",
|
520 |
+
"dataType": "sc:Boolean",
|
521 |
+
"source": {
|
522 |
+
"fileSet": {
|
523 |
+
"@id": "benchmark-cases-parquet"
|
524 |
+
},
|
525 |
+
"extract": {
|
526 |
+
"column": "transformer_cfg.use_attn_scale"
|
527 |
+
}
|
528 |
+
}
|
529 |
+
},
|
530 |
+
{
|
531 |
+
"@type": "cr:Field",
|
532 |
+
"@id": "transformer_cfg.use_split_qkv_input",
|
533 |
+
"name": "transformer_cfg.use_split_qkv_input",
|
534 |
+
"description": "Column 'transformer_cfg.use_split_qkv_input' from the parquet file describing all the cases in the benchmark.",
|
535 |
+
"dataType": "sc:Boolean",
|
536 |
+
"source": {
|
537 |
+
"fileSet": {
|
538 |
+
"@id": "benchmark-cases-parquet"
|
539 |
+
},
|
540 |
+
"extract": {
|
541 |
+
"column": "transformer_cfg.use_split_qkv_input"
|
542 |
+
}
|
543 |
+
}
|
544 |
+
},
|
545 |
+
{
|
546 |
+
"@type": "cr:Field",
|
547 |
+
"@id": "transformer_cfg.use_hook_mlp_in",
|
548 |
+
"name": "transformer_cfg.use_hook_mlp_in",
|
549 |
+
"description": "Column 'transformer_cfg.use_hook_mlp_in' from the parquet file describing all the cases in the benchmark.",
|
550 |
+
"dataType": "sc:Boolean",
|
551 |
+
"source": {
|
552 |
+
"fileSet": {
|
553 |
+
"@id": "benchmark-cases-parquet"
|
554 |
+
},
|
555 |
+
"extract": {
|
556 |
+
"column": "transformer_cfg.use_hook_mlp_in"
|
557 |
+
}
|
558 |
+
}
|
559 |
+
},
|
560 |
+
{
|
561 |
+
"@type": "cr:Field",
|
562 |
+
"@id": "transformer_cfg.use_attn_in",
|
563 |
+
"name": "transformer_cfg.use_attn_in",
|
564 |
+
"description": "Column 'transformer_cfg.use_attn_in' from the parquet file describing all the cases in the benchmark.",
|
565 |
+
"dataType": "sc:Boolean",
|
566 |
+
"source": {
|
567 |
+
"fileSet": {
|
568 |
+
"@id": "benchmark-cases-parquet"
|
569 |
+
},
|
570 |
+
"extract": {
|
571 |
+
"column": "transformer_cfg.use_attn_in"
|
572 |
+
}
|
573 |
+
}
|
574 |
+
},
|
575 |
+
{
|
576 |
+
"@type": "cr:Field",
|
577 |
+
"@id": "transformer_cfg.use_local_attn",
|
578 |
+
"name": "transformer_cfg.use_local_attn",
|
579 |
+
"description": "Column 'transformer_cfg.use_local_attn' from the parquet file describing all the cases in the benchmark.",
|
580 |
+
"dataType": "sc:Boolean",
|
581 |
+
"source": {
|
582 |
+
"fileSet": {
|
583 |
+
"@id": "benchmark-cases-parquet"
|
584 |
+
},
|
585 |
+
"extract": {
|
586 |
+
"column": "transformer_cfg.use_local_attn"
|
587 |
+
}
|
588 |
+
}
|
589 |
+
},
|
590 |
+
{
|
591 |
+
"@type": "cr:Field",
|
592 |
+
"@id": "transformer_cfg.original_architecture",
|
593 |
+
"name": "transformer_cfg.original_architecture",
|
594 |
+
"description": "Column 'transformer_cfg.original_architecture' from the parquet file describing all the cases in the benchmark.",
|
595 |
+
"dataType": "sc:Float",
|
596 |
+
"source": {
|
597 |
+
"fileSet": {
|
598 |
+
"@id": "benchmark-cases-parquet"
|
599 |
+
},
|
600 |
+
"extract": {
|
601 |
+
"column": "transformer_cfg.original_architecture"
|
602 |
+
}
|
603 |
+
}
|
604 |
+
},
|
605 |
+
{
|
606 |
+
"@type": "cr:Field",
|
607 |
+
"@id": "transformer_cfg.from_checkpoint",
|
608 |
+
"name": "transformer_cfg.from_checkpoint",
|
609 |
+
"description": "Column 'transformer_cfg.from_checkpoint' from the parquet file describing all the cases in the benchmark.",
|
610 |
+
"dataType": "sc:Boolean",
|
611 |
+
"source": {
|
612 |
+
"fileSet": {
|
613 |
+
"@id": "benchmark-cases-parquet"
|
614 |
+
},
|
615 |
+
"extract": {
|
616 |
+
"column": "transformer_cfg.from_checkpoint"
|
617 |
+
}
|
618 |
+
}
|
619 |
+
},
|
620 |
+
{
|
621 |
+
"@type": "cr:Field",
|
622 |
+
"@id": "transformer_cfg.checkpoint_index",
|
623 |
+
"name": "transformer_cfg.checkpoint_index",
|
624 |
+
"description": "Column 'transformer_cfg.checkpoint_index' from the parquet file describing all the cases in the benchmark.",
|
625 |
+
"dataType": "sc:Float",
|
626 |
+
"source": {
|
627 |
+
"fileSet": {
|
628 |
+
"@id": "benchmark-cases-parquet"
|
629 |
+
},
|
630 |
+
"extract": {
|
631 |
+
"column": "transformer_cfg.checkpoint_index"
|
632 |
+
}
|
633 |
+
}
|
634 |
+
},
|
635 |
+
{
|
636 |
+
"@type": "cr:Field",
|
637 |
+
"@id": "transformer_cfg.checkpoint_label_type",
|
638 |
+
"name": "transformer_cfg.checkpoint_label_type",
|
639 |
+
"description": "Column 'transformer_cfg.checkpoint_label_type' from the parquet file describing all the cases in the benchmark.",
|
640 |
+
"dataType": "sc:Float",
|
641 |
+
"source": {
|
642 |
+
"fileSet": {
|
643 |
+
"@id": "benchmark-cases-parquet"
|
644 |
+
},
|
645 |
+
"extract": {
|
646 |
+
"column": "transformer_cfg.checkpoint_label_type"
|
647 |
+
}
|
648 |
+
}
|
649 |
+
},
|
650 |
+
{
|
651 |
+
"@type": "cr:Field",
|
652 |
+
"@id": "transformer_cfg.checkpoint_value",
|
653 |
+
"name": "transformer_cfg.checkpoint_value",
|
654 |
+
"description": "Column 'transformer_cfg.checkpoint_value' from the parquet file describing all the cases in the benchmark.",
|
655 |
+
"dataType": "sc:Float",
|
656 |
+
"source": {
|
657 |
+
"fileSet": {
|
658 |
+
"@id": "benchmark-cases-parquet"
|
659 |
+
},
|
660 |
+
"extract": {
|
661 |
+
"column": "transformer_cfg.checkpoint_value"
|
662 |
+
}
|
663 |
+
}
|
664 |
+
},
|
665 |
+
{
|
666 |
+
"@type": "cr:Field",
|
667 |
+
"@id": "transformer_cfg.tokenizer_name",
|
668 |
+
"name": "transformer_cfg.tokenizer_name",
|
669 |
+
"description": "Column 'transformer_cfg.tokenizer_name' from the parquet file describing all the cases in the benchmark.",
|
670 |
+
"dataType": "sc:Float",
|
671 |
+
"source": {
|
672 |
+
"fileSet": {
|
673 |
+
"@id": "benchmark-cases-parquet"
|
674 |
+
},
|
675 |
+
"extract": {
|
676 |
+
"column": "transformer_cfg.tokenizer_name"
|
677 |
+
}
|
678 |
+
}
|
679 |
+
},
|
680 |
+
{
|
681 |
+
"@type": "cr:Field",
|
682 |
+
"@id": "transformer_cfg.window_size",
|
683 |
+
"name": "transformer_cfg.window_size",
|
684 |
+
"description": "Column 'transformer_cfg.window_size' from the parquet file describing all the cases in the benchmark.",
|
685 |
+
"dataType": "sc:Float",
|
686 |
+
"source": {
|
687 |
+
"fileSet": {
|
688 |
+
"@id": "benchmark-cases-parquet"
|
689 |
+
},
|
690 |
+
"extract": {
|
691 |
+
"column": "transformer_cfg.window_size"
|
692 |
+
}
|
693 |
+
}
|
694 |
+
},
|
695 |
+
{
|
696 |
+
"@type": "cr:Field",
|
697 |
+
"@id": "transformer_cfg.attn_types",
|
698 |
+
"name": "transformer_cfg.attn_types",
|
699 |
+
"description": "Column 'transformer_cfg.attn_types' from the parquet file describing all the cases in the benchmark.",
|
700 |
+
"dataType": "sc:Float",
|
701 |
+
"source": {
|
702 |
+
"fileSet": {
|
703 |
+
"@id": "benchmark-cases-parquet"
|
704 |
+
},
|
705 |
+
"extract": {
|
706 |
+
"column": "transformer_cfg.attn_types"
|
707 |
+
}
|
708 |
+
}
|
709 |
+
},
|
710 |
+
{
|
711 |
+
"@type": "cr:Field",
|
712 |
+
"@id": "transformer_cfg.init_mode",
|
713 |
+
"name": "transformer_cfg.init_mode",
|
714 |
+
"description": "Column 'transformer_cfg.init_mode' from the parquet file describing all the cases in the benchmark.",
|
715 |
+
"dataType": "sc:Text",
|
716 |
+
"source": {
|
717 |
+
"fileSet": {
|
718 |
+
"@id": "benchmark-cases-parquet"
|
719 |
+
},
|
720 |
+
"extract": {
|
721 |
+
"column": "transformer_cfg.init_mode"
|
722 |
+
}
|
723 |
+
}
|
724 |
+
},
|
725 |
+
{
|
726 |
+
"@type": "cr:Field",
|
727 |
+
"@id": "transformer_cfg.normalization_type",
|
728 |
+
"name": "transformer_cfg.normalization_type",
|
729 |
+
"description": "Column 'transformer_cfg.normalization_type' from the parquet file describing all the cases in the benchmark.",
|
730 |
+
"dataType": "sc:Float",
|
731 |
+
"source": {
|
732 |
+
"fileSet": {
|
733 |
+
"@id": "benchmark-cases-parquet"
|
734 |
+
},
|
735 |
+
"extract": {
|
736 |
+
"column": "transformer_cfg.normalization_type"
|
737 |
+
}
|
738 |
+
}
|
739 |
+
},
|
740 |
+
{
|
741 |
+
"@type": "cr:Field",
|
742 |
+
"@id": "transformer_cfg.device",
|
743 |
+
"name": "transformer_cfg.device",
|
744 |
+
"description": "Column 'transformer_cfg.device' from the parquet file describing all the cases in the benchmark.",
|
745 |
+
"dataType": "sc:Text",
|
746 |
+
"source": {
|
747 |
+
"fileSet": {
|
748 |
+
"@id": "benchmark-cases-parquet"
|
749 |
+
},
|
750 |
+
"extract": {
|
751 |
+
"column": "transformer_cfg.device"
|
752 |
+
}
|
753 |
+
}
|
754 |
+
},
|
755 |
+
{
|
756 |
+
"@type": "cr:Field",
|
757 |
+
"@id": "transformer_cfg.n_devices",
|
758 |
+
"name": "transformer_cfg.n_devices",
|
759 |
+
"description": "Column 'transformer_cfg.n_devices' from the parquet file describing all the cases in the benchmark.",
|
760 |
+
"dataType": "sc:Float",
|
761 |
+
"source": {
|
762 |
+
"fileSet": {
|
763 |
+
"@id": "benchmark-cases-parquet"
|
764 |
+
},
|
765 |
+
"extract": {
|
766 |
+
"column": "transformer_cfg.n_devices"
|
767 |
+
}
|
768 |
+
}
|
769 |
+
},
|
770 |
+
{
|
771 |
+
"@type": "cr:Field",
|
772 |
+
"@id": "transformer_cfg.attention_dir",
|
773 |
+
"name": "transformer_cfg.attention_dir",
|
774 |
+
"description": "Column 'transformer_cfg.attention_dir' from the parquet file describing all the cases in the benchmark.",
|
775 |
+
"dataType": "sc:Text",
|
776 |
+
"source": {
|
777 |
+
"fileSet": {
|
778 |
+
"@id": "benchmark-cases-parquet"
|
779 |
+
},
|
780 |
+
"extract": {
|
781 |
+
"column": "transformer_cfg.attention_dir"
|
782 |
+
}
|
783 |
+
}
|
784 |
+
},
|
785 |
+
{
|
786 |
+
"@type": "cr:Field",
|
787 |
+
"@id": "transformer_cfg.attn_only",
|
788 |
+
"name": "transformer_cfg.attn_only",
|
789 |
+
"description": "Column 'transformer_cfg.attn_only' from the parquet file describing all the cases in the benchmark.",
|
790 |
+
"dataType": "sc:Boolean",
|
791 |
+
"source": {
|
792 |
+
"fileSet": {
|
793 |
+
"@id": "benchmark-cases-parquet"
|
794 |
+
},
|
795 |
+
"extract": {
|
796 |
+
"column": "transformer_cfg.attn_only"
|
797 |
+
}
|
798 |
+
}
|
799 |
+
},
|
800 |
+
{
|
801 |
+
"@type": "cr:Field",
|
802 |
+
"@id": "transformer_cfg.seed",
|
803 |
+
"name": "transformer_cfg.seed",
|
804 |
+
"description": "Column 'transformer_cfg.seed' from the parquet file describing all the cases in the benchmark.",
|
805 |
+
"dataType": "sc:Float",
|
806 |
+
"source": {
|
807 |
+
"fileSet": {
|
808 |
+
"@id": "benchmark-cases-parquet"
|
809 |
+
},
|
810 |
+
"extract": {
|
811 |
+
"column": "transformer_cfg.seed"
|
812 |
+
}
|
813 |
+
}
|
814 |
+
},
|
815 |
+
{
|
816 |
+
"@type": "cr:Field",
|
817 |
+
"@id": "transformer_cfg.initializer_range",
|
818 |
+
"name": "transformer_cfg.initializer_range",
|
819 |
+
"description": "Column 'transformer_cfg.initializer_range' from the parquet file describing all the cases in the benchmark.",
|
820 |
+
"dataType": "sc:Float",
|
821 |
+
"source": {
|
822 |
+
"fileSet": {
|
823 |
+
"@id": "benchmark-cases-parquet"
|
824 |
+
},
|
825 |
+
"extract": {
|
826 |
+
"column": "transformer_cfg.initializer_range"
|
827 |
+
}
|
828 |
+
}
|
829 |
+
},
|
830 |
+
{
|
831 |
+
"@type": "cr:Field",
|
832 |
+
"@id": "transformer_cfg.init_weights",
|
833 |
+
"name": "transformer_cfg.init_weights",
|
834 |
+
"description": "Column 'transformer_cfg.init_weights' from the parquet file describing all the cases in the benchmark.",
|
835 |
+
"dataType": "sc:Boolean",
|
836 |
+
"source": {
|
837 |
+
"fileSet": {
|
838 |
+
"@id": "benchmark-cases-parquet"
|
839 |
+
},
|
840 |
+
"extract": {
|
841 |
+
"column": "transformer_cfg.init_weights"
|
842 |
+
}
|
843 |
+
}
|
844 |
+
},
|
845 |
+
{
|
846 |
+
"@type": "cr:Field",
|
847 |
+
"@id": "transformer_cfg.scale_attn_by_inverse_layer_idx",
|
848 |
+
"name": "transformer_cfg.scale_attn_by_inverse_layer_idx",
|
849 |
+
"description": "Column 'transformer_cfg.scale_attn_by_inverse_layer_idx' from the parquet file describing all the cases in the benchmark.",
|
850 |
+
"dataType": "sc:Boolean",
|
851 |
+
"source": {
|
852 |
+
"fileSet": {
|
853 |
+
"@id": "benchmark-cases-parquet"
|
854 |
+
},
|
855 |
+
"extract": {
|
856 |
+
"column": "transformer_cfg.scale_attn_by_inverse_layer_idx"
|
857 |
+
}
|
858 |
+
}
|
859 |
+
},
|
860 |
+
{
|
861 |
+
"@type": "cr:Field",
|
862 |
+
"@id": "transformer_cfg.positional_embedding_type",
|
863 |
+
"name": "transformer_cfg.positional_embedding_type",
|
864 |
+
"description": "Column 'transformer_cfg.positional_embedding_type' from the parquet file describing all the cases in the benchmark.",
|
865 |
+
"dataType": "sc:Text",
|
866 |
+
"source": {
|
867 |
+
"fileSet": {
|
868 |
+
"@id": "benchmark-cases-parquet"
|
869 |
+
},
|
870 |
+
"extract": {
|
871 |
+
"column": "transformer_cfg.positional_embedding_type"
|
872 |
+
}
|
873 |
+
}
|
874 |
+
},
|
875 |
+
{
|
876 |
+
"@type": "cr:Field",
|
877 |
+
"@id": "transformer_cfg.final_rms",
|
878 |
+
"name": "transformer_cfg.final_rms",
|
879 |
+
"description": "Column 'transformer_cfg.final_rms' from the parquet file describing all the cases in the benchmark.",
|
880 |
+
"dataType": "sc:Boolean",
|
881 |
+
"source": {
|
882 |
+
"fileSet": {
|
883 |
+
"@id": "benchmark-cases-parquet"
|
884 |
+
},
|
885 |
+
"extract": {
|
886 |
+
"column": "transformer_cfg.final_rms"
|
887 |
+
}
|
888 |
+
}
|
889 |
+
},
|
890 |
+
{
|
891 |
+
"@type": "cr:Field",
|
892 |
+
"@id": "transformer_cfg.d_vocab_out",
|
893 |
+
"name": "transformer_cfg.d_vocab_out",
|
894 |
+
"description": "Column 'transformer_cfg.d_vocab_out' from the parquet file describing all the cases in the benchmark.",
|
895 |
+
"dataType": "sc:Float",
|
896 |
+
"source": {
|
897 |
+
"fileSet": {
|
898 |
+
"@id": "benchmark-cases-parquet"
|
899 |
+
},
|
900 |
+
"extract": {
|
901 |
+
"column": "transformer_cfg.d_vocab_out"
|
902 |
+
}
|
903 |
+
}
|
904 |
+
},
|
905 |
+
{
|
906 |
+
"@type": "cr:Field",
|
907 |
+
"@id": "transformer_cfg.parallel_attn_mlp",
|
908 |
+
"name": "transformer_cfg.parallel_attn_mlp",
|
909 |
+
"description": "Column 'transformer_cfg.parallel_attn_mlp' from the parquet file describing all the cases in the benchmark.",
|
910 |
+
"dataType": "sc:Boolean",
|
911 |
+
"source": {
|
912 |
+
"fileSet": {
|
913 |
+
"@id": "benchmark-cases-parquet"
|
914 |
+
},
|
915 |
+
"extract": {
|
916 |
+
"column": "transformer_cfg.parallel_attn_mlp"
|
917 |
+
}
|
918 |
+
}
|
919 |
+
},
|
920 |
+
{
|
921 |
+
"@type": "cr:Field",
|
922 |
+
"@id": "transformer_cfg.rotary_dim",
|
923 |
+
"name": "transformer_cfg.rotary_dim",
|
924 |
+
"description": "Column 'transformer_cfg.rotary_dim' from the parquet file describing all the cases in the benchmark.",
|
925 |
+
"dataType": "sc:Float",
|
926 |
+
"source": {
|
927 |
+
"fileSet": {
|
928 |
+
"@id": "benchmark-cases-parquet"
|
929 |
+
},
|
930 |
+
"extract": {
|
931 |
+
"column": "transformer_cfg.rotary_dim"
|
932 |
+
}
|
933 |
+
}
|
934 |
+
},
|
935 |
+
{
|
936 |
+
"@type": "cr:Field",
|
937 |
+
"@id": "transformer_cfg.n_params",
|
938 |
+
"name": "transformer_cfg.n_params",
|
939 |
+
"description": "Column 'transformer_cfg.n_params' from the parquet file describing all the cases in the benchmark.",
|
940 |
+
"dataType": "sc:Float",
|
941 |
+
"source": {
|
942 |
+
"fileSet": {
|
943 |
+
"@id": "benchmark-cases-parquet"
|
944 |
+
},
|
945 |
+
"extract": {
|
946 |
+
"column": "transformer_cfg.n_params"
|
947 |
+
}
|
948 |
+
}
|
949 |
+
},
|
950 |
+
{
|
951 |
+
"@type": "cr:Field",
|
952 |
+
"@id": "transformer_cfg.use_hook_tokens",
|
953 |
+
"name": "transformer_cfg.use_hook_tokens",
|
954 |
+
"description": "Column 'transformer_cfg.use_hook_tokens' from the parquet file describing all the cases in the benchmark.",
|
955 |
+
"dataType": "sc:Boolean",
|
956 |
+
"source": {
|
957 |
+
"fileSet": {
|
958 |
+
"@id": "benchmark-cases-parquet"
|
959 |
+
},
|
960 |
+
"extract": {
|
961 |
+
"column": "transformer_cfg.use_hook_tokens"
|
962 |
+
}
|
963 |
+
}
|
964 |
+
},
|
965 |
+
{
|
966 |
+
"@type": "cr:Field",
|
967 |
+
"@id": "transformer_cfg.gated_mlp",
|
968 |
+
"name": "transformer_cfg.gated_mlp",
|
969 |
+
"description": "Column 'transformer_cfg.gated_mlp' from the parquet file describing all the cases in the benchmark.",
|
970 |
+
"dataType": "sc:Boolean",
|
971 |
+
"source": {
|
972 |
+
"fileSet": {
|
973 |
+
"@id": "benchmark-cases-parquet"
|
974 |
+
},
|
975 |
+
"extract": {
|
976 |
+
"column": "transformer_cfg.gated_mlp"
|
977 |
+
}
|
978 |
+
}
|
979 |
+
},
|
980 |
+
{
|
981 |
+
"@type": "cr:Field",
|
982 |
+
"@id": "transformer_cfg.default_prepend_bos",
|
983 |
+
"name": "transformer_cfg.default_prepend_bos",
|
984 |
+
"description": "Column 'transformer_cfg.default_prepend_bos' from the parquet file describing all the cases in the benchmark.",
|
985 |
+
"dataType": "sc:Boolean",
|
986 |
+
"source": {
|
987 |
+
"fileSet": {
|
988 |
+
"@id": "benchmark-cases-parquet"
|
989 |
+
},
|
990 |
+
"extract": {
|
991 |
+
"column": "transformer_cfg.default_prepend_bos"
|
992 |
+
}
|
993 |
+
}
|
994 |
+
},
|
995 |
+
{
|
996 |
+
"@type": "cr:Field",
|
997 |
+
"@id": "transformer_cfg.dtype",
|
998 |
+
"name": "transformer_cfg.dtype",
|
999 |
+
"description": "Column 'transformer_cfg.dtype' from the parquet file describing all the cases in the benchmark.",
|
1000 |
+
"dataType": "sc:Text",
|
1001 |
+
"source": {
|
1002 |
+
"fileSet": {
|
1003 |
+
"@id": "benchmark-cases-parquet"
|
1004 |
+
},
|
1005 |
+
"extract": {
|
1006 |
+
"column": "transformer_cfg.dtype"
|
1007 |
+
}
|
1008 |
+
}
|
1009 |
+
},
|
1010 |
+
{
|
1011 |
+
"@type": "cr:Field",
|
1012 |
+
"@id": "transformer_cfg.tokenizer_prepends_bos",
|
1013 |
+
"name": "transformer_cfg.tokenizer_prepends_bos",
|
1014 |
+
"description": "Column 'transformer_cfg.tokenizer_prepends_bos' from the parquet file describing all the cases in the benchmark.",
|
1015 |
+
"dataType": "sc:Float",
|
1016 |
+
"source": {
|
1017 |
+
"fileSet": {
|
1018 |
+
"@id": "benchmark-cases-parquet"
|
1019 |
+
},
|
1020 |
+
"extract": {
|
1021 |
+
"column": "transformer_cfg.tokenizer_prepends_bos"
|
1022 |
+
}
|
1023 |
+
}
|
1024 |
+
},
|
1025 |
+
{
|
1026 |
+
"@type": "cr:Field",
|
1027 |
+
"@id": "transformer_cfg.n_key_value_heads",
|
1028 |
+
"name": "transformer_cfg.n_key_value_heads",
|
1029 |
+
"description": "Column 'transformer_cfg.n_key_value_heads' from the parquet file describing all the cases in the benchmark.",
|
1030 |
+
"dataType": "sc:Float",
|
1031 |
+
"source": {
|
1032 |
+
"fileSet": {
|
1033 |
+
"@id": "benchmark-cases-parquet"
|
1034 |
+
},
|
1035 |
+
"extract": {
|
1036 |
+
"column": "transformer_cfg.n_key_value_heads"
|
1037 |
+
}
|
1038 |
+
}
|
1039 |
+
},
|
1040 |
+
{
|
1041 |
+
"@type": "cr:Field",
|
1042 |
+
"@id": "transformer_cfg.post_embedding_ln",
|
1043 |
+
"name": "transformer_cfg.post_embedding_ln",
|
1044 |
+
"description": "Column 'transformer_cfg.post_embedding_ln' from the parquet file describing all the cases in the benchmark.",
|
1045 |
+
"dataType": "sc:Boolean",
|
1046 |
+
"source": {
|
1047 |
+
"fileSet": {
|
1048 |
+
"@id": "benchmark-cases-parquet"
|
1049 |
+
},
|
1050 |
+
"extract": {
|
1051 |
+
"column": "transformer_cfg.post_embedding_ln"
|
1052 |
+
}
|
1053 |
+
}
|
1054 |
+
},
|
1055 |
+
{
|
1056 |
+
"@type": "cr:Field",
|
1057 |
+
"@id": "transformer_cfg.rotary_base",
|
1058 |
+
"name": "transformer_cfg.rotary_base",
|
1059 |
+
"description": "Column 'transformer_cfg.rotary_base' from the parquet file describing all the cases in the benchmark.",
|
1060 |
+
"dataType": "sc:Float",
|
1061 |
+
"source": {
|
1062 |
+
"fileSet": {
|
1063 |
+
"@id": "benchmark-cases-parquet"
|
1064 |
+
},
|
1065 |
+
"extract": {
|
1066 |
+
"column": "transformer_cfg.rotary_base"
|
1067 |
+
}
|
1068 |
+
}
|
1069 |
+
},
|
1070 |
+
{
|
1071 |
+
"@type": "cr:Field",
|
1072 |
+
"@id": "transformer_cfg.trust_remote_code",
|
1073 |
+
"name": "transformer_cfg.trust_remote_code",
|
1074 |
+
"description": "Column 'transformer_cfg.trust_remote_code' from the parquet file describing all the cases in the benchmark.",
|
1075 |
+
"dataType": "sc:Boolean",
|
1076 |
+
"source": {
|
1077 |
+
"fileSet": {
|
1078 |
+
"@id": "benchmark-cases-parquet"
|
1079 |
+
},
|
1080 |
+
"extract": {
|
1081 |
+
"column": "transformer_cfg.trust_remote_code"
|
1082 |
+
}
|
1083 |
+
}
|
1084 |
+
},
|
1085 |
+
{
|
1086 |
+
"@type": "cr:Field",
|
1087 |
+
"@id": "transformer_cfg.rotary_adjacent_pairs",
|
1088 |
+
"name": "transformer_cfg.rotary_adjacent_pairs",
|
1089 |
+
"description": "Column 'transformer_cfg.rotary_adjacent_pairs' from the parquet file describing all the cases in the benchmark.",
|
1090 |
+
"dataType": "sc:Boolean",
|
1091 |
+
"source": {
|
1092 |
+
"fileSet": {
|
1093 |
+
"@id": "benchmark-cases-parquet"
|
1094 |
+
},
|
1095 |
+
"extract": {
|
1096 |
+
"column": "transformer_cfg.rotary_adjacent_pairs"
|
1097 |
+
}
|
1098 |
+
}
|
1099 |
+
}
|
1100 |
+
]
|
1101 |
+
}
|
1102 |
+
]
|
1103 |
+
}
|