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neginashz
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star-sft-intellect-instruct-2

Text Generation
Transformers
PyTorch
Safetensors
llama
axolotl
Generated from Trainer
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +186 -0
  2. generation_config.json +8 -0
  3. pytorch_model-00001-of-00002.bin +3 -0
  4. pytorch_model-00002-of-00002.bin +3 -0
  5. pytorch_model.bin.index.json +388 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: PrimeIntellect/INTELLECT-1-Instruct
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ datasets:
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+ - neginashz/rationale-llama-chat-dataset
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+ model-index:
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+ - name: star-sft-intellect-instruct-2
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+ results: []
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+ ---
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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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+
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+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.6.0`
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+ ```yaml
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+ base_model: PrimeIntellect/INTELLECT-1-Instruct
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+ trust_remote_code: true
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ gpu_memory_limit:
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+
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+ load_in_8bit:
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+ load_in_4bit:
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+ strict: false
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+
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+ chat_template: llama3
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+ datasets:
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+ - path: neginashz/rationale-llama-chat-dataset
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+ type: chat_template
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+ field_messages: messages
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+ message_field_role: role
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+ message_field_content: content
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+
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+
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+ dataset_prepared_path:
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+ val_set_size: 0.1
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+ output_dir: ./star-sft-intellect-2
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+
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+
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+
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+
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+ sequence_len: 8192
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+ sample_packing: true
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+ eval_sample_packing: true
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+ pad_to_sequence_len: true
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+
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+
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+ wandb_project: star-sft-intellect-instruct-2
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name:
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+ wandb_log_model:
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+
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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_torch
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+ lr_scheduler: cosine
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+ learning_rate: 0.00002
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: true
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+ fp16: false
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+ tf32: false
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+
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+ gradient_checkpointing: true
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+
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+
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+ warmup_steps:
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+ eval_steps:
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+ save_steps:
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+
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+ evals_per_epoch: 16
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+ saves_per_epoch: 1
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+
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+ debug:
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+ deepspeed: deepspeed_configs/zero2.json
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+ weight_decay:
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ pad_token: <|end_of_text|>
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+ pad_token: <|finetune_right_pad_id|>
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+
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+ hub_model_id: neginashz/star-sft-intellect-instruct-2
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+ hub_strategy:
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+ early_stopping_patience:
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+
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+ resume_from_checkpoint:
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+ auto_resume_from_checkpoints: true
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+
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+
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+
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+ ```
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+
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+ </details><br>
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+
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+ # star-sft-intellect-instruct-2
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+
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+ This model is a fine-tuned version of [PrimeIntellect/INTELLECT-1-Instruct](https://huggingface.co/PrimeIntellect/INTELLECT-1-Instruct) on the neginashz/rationale-llama-chat-dataset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3719
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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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: 4
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+ - total_train_batch_size: 4
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+ - total_eval_batch_size: 4
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 6
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.5033 | 0.0686 | 7 | 0.4057 |
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+ | 0.4303 | 0.1373 | 14 | 0.3986 |
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+ | 0.4496 | 0.2059 | 21 | 0.3977 |
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+ | 0.4223 | 0.2745 | 28 | 0.3973 |
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+ | 0.4083 | 0.3431 | 35 | 0.3940 |
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+ | 0.4191 | 0.4118 | 42 | 0.3893 |
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+ | 0.412 | 0.4804 | 49 | 0.3859 |
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+ | 0.3912 | 0.5490 | 56 | 0.3812 |
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+ | 0.3995 | 0.6176 | 63 | 0.3749 |
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+ | 0.4236 | 0.6863 | 70 | 0.3703 |
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+ | 0.3833 | 0.7549 | 77 | 0.3663 |
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+ | 0.3605 | 0.8235 | 84 | 0.3614 |
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+ | 0.3952 | 0.8922 | 91 | 0.3576 |
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+ | 0.3744 | 0.9608 | 98 | 0.3540 |
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+ | 0.199 | 1.0196 | 105 | 0.3536 |
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+ | 0.1762 | 1.0882 | 112 | 0.4128 |
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+ | 0.1704 | 1.1569 | 119 | 0.3808 |
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+ | 0.1603 | 1.2255 | 126 | 0.3781 |
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+ | 0.1727 | 1.2941 | 133 | 0.3874 |
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+ | 0.1624 | 1.3627 | 140 | 0.3841 |
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+ | 0.1546 | 1.4314 | 147 | 0.3793 |
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+ | 0.1602 | 1.5 | 154 | 0.3776 |
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+ | 0.1501 | 1.5686 | 161 | 0.3745 |
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+ | 0.146 | 1.6373 | 168 | 0.3734 |
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+ | 0.1512 | 1.7059 | 175 | 0.3733 |
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+ | 0.146 | 1.7745 | 182 | 0.3725 |
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+ | 0.1479 | 1.8431 | 189 | 0.3721 |
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+ | 0.1395 | 1.9118 | 196 | 0.3720 |
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+ | 0.1472 | 1.9804 | 203 | 0.3719 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.21.0
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+ "do_sample": true,
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+ "eos_token_id": 128009,
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+ "transformers_version": "4.47.0",
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+ "use_cache": false
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+ }
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