Upload 9 files
Browse files- README.md +23 -11
- added_tokens.json +4 -0
- config.json +5 -5
- generation_config.json +3 -3
- model.safetensors.index.json +1 -1
- special_tokens_map.json +19 -15
- tokenizer.json +2 -2
- tokenizer_config.json +28 -4
README.md
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language:
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- multilingual
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datasets:
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- mlabonne/
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- mlabonne/harmful_behaviors
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library_name: transformers
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license: gemma
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license_link: https://ai.google.dev/gemma/terms
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@@ -40,13 +39,21 @@ described by mlabonne.
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Layer 17 of the original model was chosen for abliteration.
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I also created another layer 18 abliterated model for comparison.
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These two layers were chosen due to they both produce uncensored response
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after respective layer was abliterated.
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is compared to the original model.
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## Benchmark (100.0*raw scores only)
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| Model | Average | IFEval | BHH | Math Lv5 | GPQA | MUSR | MMLU-PRO |
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| ----- | ------- | ------ | ----|--------- | ---- | ---- | -------- |
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| [gemma-2-2b-jpn-it](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/google/gemma-2-2b-jpn-it/results_2024-10-15T15-21-39.173019.json) | 30.82 | 54.11 | 41.43 | 0.0 | 27.52 | 37.17 | 24.67 |
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| [gemma-2-2b-jpn-it-abliterated-17](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-17/results_2024-10-18T15-18-46.821674.json) | 30.29 | 52.65 | 40.46 | 0.0 | 27.18 | 36.90 | 24.55 |
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| [gemma-2-2b-jpn-it-abliterated-18](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-18/results_2024-10-18T15-41-42.399571.json) | 30.61 | 53.02 | 40.96 | 0.0 | 27.35 | 37.30 | 25.05 |
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## How to run this model
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import transformers
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import torch
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model_id = "gemma-2-2b-jpn-it-abliterated-17"
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dtype = torch.bfloat16
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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Then, you can target the specific file you want:
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```
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huggingface-cli download ymcki/gemma-2-2b-jpn-it-abliterated-17 --include "*" --local-dir ./
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```
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## Credits
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Thank you mlabonne for describing his
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language:
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- multilingual
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datasets:
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- mlabonne/orpo-dpo-mix-40k
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library_name: transformers
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license: gemma
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license_link: https://ai.google.dev/gemma/terms
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Layer 17 of the original model was chosen for abliteration.
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I also created another layer 18 abliterated model for comparison.
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ORPO fine tuning was performed for eight epoches.
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| Epoch | loss | eval_loss |
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| ----- | ---- | --------- |
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| 1 | 1.20152769684791564 | 1.0501047372817993 |
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| 2 | 1.25755584239959716 | 1.0144596099853516 |
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| 3 | 0.93099724054336543 | 0.9957754611968994 |
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| 4 | 0.88664623498916623 | 0.9857067465782166 |
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| 5 | 0.86961059570312504 | 1.0203918218612670 |
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| 6 | 0.98065975904464630 | 0.9958684444427490 |
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| 7 | 0.38512575328350068 | 0.9686505198478699 |
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| 8 | 1.41178888082504270 | 0.9652527570724487 |
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The fine tuned model is uploaded here to be evaluated by the Open LLM Leaderboard to see if the slightly brain damaged non-ORPO model can be healed. Again, the fine tuning method is also based on one described by [mlabonne](https://towardsdatascience.com/fine-tune-llama-3-with-orpo-56cfab2f9ada) but the input model was read into VRAM by [unsloth](https://github.com/unslothai/unsloth) to allow using the full 40k dataset to run on a single 3090.
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## Benchmark (100.0*raw scores only)
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| Model | Average | IFEval | BHH | Math Lv5 | GPQA | MUSR | MMLU-PRO |
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| ----- | ------- | ------ | ----|--------- | ---- | ---- | -------- |
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| [gemma-2-2b-jpn-it](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/google/gemma-2-2b-jpn-it/results_2024-10-15T15-21-39.173019.json) | 30.82 | 54.11 | 41.43 | 0.0 | 27.52 | 37.17 | 24.67 |
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| [gemma-2-2b-jpn-it-abliterated-17-ORPO (4 epoches)](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-17-ORPO/results_2024-10-20T02-46-59.069357.json) | 29.99 | 50.94 | 38.59 | 2.87 | 27.43 | 38.23 | 21.86 |
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| gemma-2-2b-jpn-it-abliterated-17-ORPO (8 epoches) | TBD | TBD | TBD | TBD | TBD | TBD | TBD |
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| [gemma-2-2b-jpn-it-abliterated-18-ORPO (4 epoches)](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-18-ORPO/results_2024-10-22T04-04-56.385050.json) | 29.94 | 48.97 | 40.18 | 3.02 | 26.17 | 39.42 | 21.85 |
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| [gemma-2-2b-jpn-it-abliterated-17](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-17/results_2024-10-18T15-18-46.821674.json) | 30.29 | 52.65 | 40.46 | 0.0 | 27.18 | 36.90 | 24.55 |
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| [gemma-2-2b-jpn-it-abliterated-18](https://huggingface.co/datasets/open-llm-leaderboard/results/raw/main/ymcki/gemma-2-2b-jpn-it-abliterated-18/results_2024-10-18T15-41-42.399571.json) | 30.61 | 53.02 | 40.96 | 0.0 | 27.35 | 37.30 | 25.05 |
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Looks like fine tuning is probably not enough. May need to run more epoches.
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## How to run this model
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import transformers
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import torch
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model_id = "gemma-2-2b-jpn-it-abliterated-17-ORPO"
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dtype = torch.bfloat16
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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Then, you can target the specific file you want:
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```
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huggingface-cli download ymcki/gemma-2-2b-jpn-it-abliterated-17-ORPO --include "*" --local-dir ./
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```
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## Credits
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Thank you mlabonne for describing his fine tuning method.
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Thanks FullOf_Bad_Ideas from LocalLlama for the suggestion of using unsloth to save VRAM.
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added_tokens.json
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{
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"<|im_end|>": 256001,
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"<|im_start|>": 256000
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}
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"Gemma2ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"attn_logit_softcapping": 50.0,
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"bos_token_id":
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"cache_implementation": "hybrid",
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"dtype": "bfloat16",
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"eos_token_id":
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"final_logit_softcapping": 30.0,
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"head_dim": 256,
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"hidden_activation": "gelu_pytorch_tanh",
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"num_attention_heads": 8,
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"num_hidden_layers": 26,
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"num_key_value_heads": 4,
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"pad_token_id":
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"query_pre_attn_scalar": 224,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.45.2",
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"use_cache": true,
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"vocab_size":
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}
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"_name_or_path": "gemma-2-2b-jpn-it-abliterated-17",
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"architectures": [
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"Gemma2ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"attn_logit_softcapping": 50.0,
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"bos_token_id": 256000,
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"cache_implementation": "hybrid",
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"dtype": "bfloat16",
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"eos_token_id": 256001,
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"final_logit_softcapping": 30.0,
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"head_dim": 256,
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"hidden_activation": "gelu_pytorch_tanh",
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"num_attention_heads": 8,
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"num_hidden_layers": 26,
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"num_key_value_heads": 4,
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"pad_token_id": 256001,
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"query_pre_attn_scalar": 224,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.45.2",
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"use_cache": true,
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"vocab_size": 256002
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}
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generation_config.json
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"_from_model_config": true,
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"bos_token_id":
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"cache_implementation": "hybrid",
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"eos_token_id":
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"pad_token_id":
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"transformers_version": "4.45.2"
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"_from_model_config": true,
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"bos_token_id": 256000,
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"cache_implementation": "hybrid",
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"eos_token_id": 256001,
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"pad_token_id": 256001,
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"transformers_version": "4.45.2"
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model.safetensors.index.json
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"metadata": {
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"total_size":
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"weight_map": {
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"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
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{
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"metadata": {
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"total_size": 5228692992
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"weight_map": {
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"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
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special_tokens_map.json
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"additional_special_tokens": [
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"content": "<|im_start|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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{
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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],
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"bos_token": "<|im_start|>",
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"eos_token": "<|im_end|>",
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"pad_token": "<|im_end|>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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tokenizer.json
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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 sha256:798ce05be77ad0639365c369e448442dd9a31f614551b88413d483c4d45c1839
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size 34363415
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tokenizer_config.json
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"rstrip": false,
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"single_word": false,
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"special": false
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"clean_up_tokenization_spaces": false,
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"eos_token": "
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"model_max_length": 1000000000000000019884624838656,
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "GemmaTokenizer",
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"rstrip": false,
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"single_word": false,
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"special": false
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},
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"256000": {
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"content": "<|im_start|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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"256001": {
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"special": true
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"additional_special_tokens": [
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"<|im_end|>"
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],
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"bos_token": "<|im_start|>",
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"chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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"padding_side": "left",
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "GemmaTokenizer",
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