Upload folder using huggingface_hub
Browse files- README.md +149 -0
- config.json +26 -0
- generation_config.json +7 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +44 -0
README.md
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---
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license: apache-2.0
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- generated_from_trainer
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model-index:
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- name: mistral-7B-MedText-epochs-2-lr-000002
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: mistralai/Mistral-7B-v0.1
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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is_mistral_derived_model: true
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: utrgvseniorproject/medtext
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type: completion
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.05
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output_dir: ./mistral-7B-MedText-epochs-2-lr-000002
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sequence_len: 4096
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sample_packing: true
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pad_to_sequence_len: true
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adapter:
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lora_model_dir:
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lora_r:
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lora_alpha:
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lora_dropout:
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lora_target_linear:
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lora_fan_in_fan_out:
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wandb_project: mistral-7B-MedText
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wandb_entity: utrgvmedai
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wandb_watch:
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wandb_name: mistral-7B-MedText-epochs-2-lr-000002
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 1
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num_epochs: 2
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.000002
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train_on_inputs: true
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: false
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early_stopping_patience:
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#resume_from_checkpoint: true
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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flash_attn_cross_entropy: false
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flash_attn_rms_norm: true
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flash_attn_fuse_qkv: false
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flash_attn_fuse_mlp: true
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warmup_steps: 100
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evals_per_epoch: 4
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eval_table_size:
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eval_sample_packing: False
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saves_per_epoch: 1
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debug:
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deepspeed: /home/josegomez15/axolotl/deepspeed_configs/zero2.json
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weight_decay: 0.1
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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# mistral-7B-MedText-epochs-2-lr-000002
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5485
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-06
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 8
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- total_train_batch_size: 8
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- total_eval_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.5029 | 0.02 | 1 | 1.5677 |
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| 1.5889 | 0.26 | 11 | 1.5675 |
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| 1.2972 | 0.51 | 22 | 1.5647 |
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| 1.6404 | 0.77 | 33 | 1.5587 |
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| 1.4796 | 1.02 | 44 | 1.5533 |
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| 1.428 | 1.23 | 55 | 1.5506 |
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| 1.5635 | 1.49 | 66 | 1.5492 |
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| 1.2457 | 1.74 | 77 | 1.5485 |
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### Framework versions
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- Transformers 4.38.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.17.0
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "mistralai/Mistral-7B-v0.1",
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"architectures": [
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"MistralForCausalLM"
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],
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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": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.0",
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"use_cache": false,
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"vocab_size": 32000
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"do_sample": true,
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"eos_token_id": 2,
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"transformers_version": "4.38.0"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:81d91d749cbc23d5da34e8385355709e793537b1bc3804e45747b01e2cc52bf4
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size 14483504421
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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": false,
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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": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "</s>",
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"unk_token": {
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"content": "<unk>",
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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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}
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}
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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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": false,
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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": false,
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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": false,
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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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"additional_special_tokens": [],
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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": true,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "</s>",
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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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"use_fast": true
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}
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