Training in progress, step 19
Browse files- README.md +155 -0
- adapter_config.json +34 -0
- adapter_model.bin +3 -0
- adapter_model.safetensors +3 -0
- config.json +41 -0
- special_tokens_map.json +24 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: mistralai/Mistral-7B-v0.3
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model-index:
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- name: outputs/lora-out
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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-v0.3
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model_type: MistralForCausalLM
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tokenizer_type: LlamaTokenizer
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load_in_8bit: true
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load_in_4bit: false
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strict: false
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datasets:
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- path: mhenrichsen/alpaca_2k_test
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.1
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output_dir: ./outputs/lora-out
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adapter: lora
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lora_model_dir:
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sequence_len: 8192
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sample_packing: false
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pad_to_sequence_len: true
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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lora_target_modules:
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- gate_proj
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- down_proj
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- up_proj
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- q_proj
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- v_proj
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- k_proj
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- o_proj
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wandb_project: axolotl-runs
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wandb_entity: thewind-mom-finetuning
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wandb_watch:
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wandb_name: Mistral-7B-v0.3-alpaca_2k_test
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wandb_log_model:
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gradient_accumulation_steps: 4
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micro_batch_size: 2
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num_epochs: 1
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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train_on_inputs: false
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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: true
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early_stopping_patience:
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resume_from_checkpoint:
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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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loss_watchdog_threshold: 5.0
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loss_watchdog_patience: 3
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warmup_steps: 10
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evals_per_epoch: 4
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eval_table_size:
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eval_max_new_tokens: 128
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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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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# outputs/lora-out
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8745
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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: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 3
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 24
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- total_eval_batch_size: 6
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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: 10
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.2007 | 0.0133 | 1 | 1.1165 |
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| 0.9054 | 0.2533 | 19 | 0.8901 |
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| 0.8991 | 0.5067 | 38 | 0.8844 |
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| 0.7794 | 0.76 | 57 | 0.8745 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mistral-7B-v0.3",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"down_proj",
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"q_proj",
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"o_proj",
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"k_proj",
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"v_proj",
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"gate_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:91deab91f9cc247d51b6c430aade09543217a6bae87899c2827c525f6683a04a
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size 84047370
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5ea790dafbd414c541745d402bc49b6ba03af53b1b74fe13f6e0ad4d29d8dbca
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size 83945296
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config.json
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{
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"_name_or_path": "mistralai/Mistral-7B-v0.3",
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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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"quantization_config": {
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"_load_in_4bit": false,
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"_load_in_8bit": true,
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"bnb_4bit_compute_dtype": "float32",
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"bnb_4bit_quant_storage": "uint8",
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"bnb_4bit_quant_type": "fp4",
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"bnb_4bit_use_double_quant": false,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_has_fp16_weight": false,
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"llm_int8_skip_modules": null,
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"llm_int8_threshold": 6.0,
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"load_in_4bit": false,
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"load_in_8bit": true,
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"quant_method": "bitsandbytes"
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},
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.40.2",
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"use_cache": false,
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"vocab_size": 32768
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}
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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 sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
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size 587404
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tokenizer_config.json
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7f7761013b9e802718d8deba62336ab0112e8a2343a1ada3f5a93e296f6172c2
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size 5944
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