Instructions to use apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat") model = PeftModel.from_pretrained(base_model, "apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3") - Notebooks
- Google Colab
- Kaggle
| library_name: peft | |
| license: apache-2.0 | |
| base_model: unsloth/tinyllama-chat | |
| tags: | |
| - axolotl | |
| - generated_from_trainer | |
| model-index: | |
| - name: 9b7b5cec-4412-4dd7-9b96-aec92982f6c3 | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| [<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) | |
| <details><summary>See axolotl config</summary> | |
| axolotl version: `0.10.0.dev0` | |
| ```yaml | |
| adapter: lora | |
| base_model: unsloth/tinyllama-chat | |
| bf16: true | |
| datasets: | |
| - data_files: | |
| - 79e6b0a94de5b902_train_data.json | |
| ds_type: json | |
| format: custom | |
| path: /workspace/input_data/ | |
| type: | |
| field_instruction: instruct | |
| field_output: output | |
| format: '{instruction}' | |
| no_input_format: '{instruction}' | |
| system_format: '{system}' | |
| system_prompt: '' | |
| eval_max_new_tokens: 128 | |
| evals_per_epoch: 4 | |
| flash_attention: false | |
| fp16: false | |
| gradient_accumulation_steps: 1 | |
| gradient_checkpointing: true | |
| group_by_length: true | |
| hf_upload_public: true | |
| hf_upload_repo_type: model | |
| hub_model_id: apriasmoro/9b7b5cec-4412-4dd7-9b96-aec92982f6c3 | |
| learning_rate: 0.0002 | |
| load_in_4bit: false | |
| logging_steps: 10 | |
| lora_alpha: 16 | |
| lora_dropout: 0.05 | |
| lora_fan_in_fan_out: false | |
| lora_r: 8 | |
| lora_target_linear: true | |
| lr_scheduler: cosine | |
| max_steps: 2332 | |
| micro_batch_size: 60 | |
| mlflow_experiment_name: /tmp/79e6b0a94de5b902_train_data.json | |
| model_card: false | |
| optimizer: adamw_torch_fused | |
| output_dir: miner_id_24 | |
| push_to_hub: true | |
| rl: null | |
| sample_packing: true | |
| save_steps: 349 | |
| sequence_len: 2048 | |
| tf32: true | |
| tokenizer_type: AutoTokenizer | |
| train_on_inputs: true | |
| trl: null | |
| trust_remote_code: true | |
| wandb_name: 9fae32c6-0754-4762-a105-2feadb1c67e9 | |
| wandb_project: Gradients-On-Demand | |
| wandb_run: apriasmoro | |
| wandb_runid: 9fae32c6-0754-4762-a105-2feadb1c67e9 | |
| warmup_steps: 233 | |
| weight_decay: 0.02 | |
| ``` | |
| </details><br> | |
| # 9b7b5cec-4412-4dd7-9b96-aec92982f6c3 | |
| This model is a fine-tuned version of [unsloth/tinyllama-chat](https://huggingface.co/unsloth/tinyllama-chat) on an unknown dataset. | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.0002 | |
| - train_batch_size: 60 | |
| - eval_batch_size: 60 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - num_devices: 2 | |
| - total_train_batch_size: 120 | |
| - total_eval_batch_size: 120 | |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_steps: 233 | |
| - training_steps: 2332 | |
| ### Training results | |
| ### Framework versions | |
| - PEFT 0.15.2 | |
| - Transformers 4.51.3 | |
| - Pytorch 2.5.1+cu124 | |
| - Datasets 3.5.1 | |
| - Tokenizers 0.21.1 |