FluffyKaeloky
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Upload 17 files
Browse files- README.md +26 -0
- config.json +41 -0
- mergekit_config.yml +88 -0
- model.safetensors.index.json +0 -0
- output-00001-of-00009.safetensors +3 -0
- output-00002-of-00009.safetensors +3 -0
- output-00003-of-00009.safetensors +3 -0
- output-00004-of-00009.safetensors +3 -0
- output-00005-of-00009.safetensors +3 -0
- output-00006-of-00009.safetensors +3 -0
- output-00007-of-00009.safetensors +3 -0
- output-00008-of-00009.safetensors +3 -0
- output-00009-of-00009.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +42 -0
README.md
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---
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base_model:
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- jukofyork/Dark-Miqu-70B
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- sophosympatheia/Midnight-Miqu-70B-v1.5
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- jukofyork/Dawn-Miqu-70B
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library_name: transformers
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tags:
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- mergekit
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- merge
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license: other
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---
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Twilight Miqu is a Story writing model and is composed from sophosympatheia/Midnight-Miqu-70B-v1.5, jukofyork/Dawn-Miqu-70B and jukofyork/Dark-Miqu-70B
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It is an experiment to see if large models are more coherent on story writing tasks.
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Twilight = Midnight + Dawn + Dark
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Please see this model card for details and usage instructions.
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https://huggingface.co/sophosympatheia/Midnight-Miqu-70B-v1.5
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This model is based on Miqu so it's capable of 32K context.
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All miqu-derived models, including this merge, are only suitable for personal use. Mistral has been cool about it so far, but you should be aware that by downloading this merge you are assuming whatever legal risk is inherent in acquiring and using a model based on leaked weights. This merge comes with no warranties or guarantees of any kind, but you probably already knew that.
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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A big thank you to Mistral, sophosympatheia and jukofyork for the original models!
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config.json
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{
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"_name_or_path": "softwareweaver/Twilight-Miqu-146B",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 28672,
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"max_position_embeddings": 32764,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 64,
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"num_hidden_layers": 170,
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"num_key_value_heads": 8,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 1000000,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.41.1",
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"use_cache": true,
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"vocab_size": 32000,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.1.1",
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"bits": 3.75,
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"head_bits": 6,
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"calibration": {
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"rows": 100,
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"length": 2048,
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"dataset": "(default)"
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}
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}
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}
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mergekit_config.yml
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const_tag: &MODEL1 sophosympatheia/Midnight-Miqu-70B-v1.5
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const_tag: &MODEL3 jukofyork/Dawn-Miqu-70B
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const_tag: &MODEL2 jukofyork/Dark-Miqu-70B
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const_tag: &QK_ATTENUATION_FACTOR 0.8408964153 # sqrt(sqrt(1/2))
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const_tag: &MLP_DOWN_SCALE_FACTOR 0.7071067812 # sqrt(1/2)
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scale-filter-env: &scale_filter_env
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parameters:
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scale:
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- filter: q_proj
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value: *QK_ATTENUATION_FACTOR
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- filter: k_proj
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value: *QK_ATTENUATION_FACTOR
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- filter: down_proj
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value: *MLP_DOWN_SCALE_FACTOR
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- value: 1.0
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slices:
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- sources:
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- model: *MODEL1
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layer_range: [0, 10]
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- sources:
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- model: *MODEL1
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layer_range: [10, 20]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL2
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layer_range: [10, 20]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL3
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layer_range: [10, 20]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL3
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layer_range: [20, 30]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL2
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layer_range: [20, 30]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL1
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layer_range: [30, 40]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL2
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layer_range: [30, 40]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL3
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layer_range: [40, 50]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL2
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layer_range: [40, 50]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL1
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layer_range: [50, 60]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL2
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layer_range: [50, 60]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL3
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layer_range: [50, 60]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL1
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layer_range: [60, 70]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL2
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layer_range: [60, 70]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL3
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layer_range: [60, 70]
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<<: *scale_filter_env
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- sources:
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- model: *MODEL1
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layer_range: [70, 80]
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merge_method: passthrough
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dtype: float16
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model.safetensors.index.json
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output-00001-of-00009.safetensors
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output-00002-of-00009.safetensors
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output-00003-of-00009.safetensors
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output-00004-of-00009.safetensors
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output-00005-of-00009.safetensors
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output-00009-of-00009.safetensors
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version https://git-lfs.github.com/spec/v1
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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}
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}
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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size 499723
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"add_prefix_space": true,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"legacy": false,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<unk>",
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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