Instructions to use NewstaR/CNC-7b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NewstaR/CNC-7b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bn22/Mistral-7B-Instruct-v0.1-sharded") model = PeftModel.from_pretrained(base_model, "NewstaR/CNC-7b-lora") - Notebooks
- Google Colab
- Kaggle
Download training_params.json from NewstaR/CNC-7b-lora: direct link, hf CLI and curl.
- Browser
- Download file 1.26 kB
-
https://huggingface.co/NewstaR/CNC-7b-lora/resolve/main/training_params.json
- Command line
-
hf download hf://NewstaR/CNC-7b-lora/training_params.json
-
curl -L -o training_params.json https://huggingface.co/NewstaR/CNC-7b-lora/resolve/main/training_params.json
1.26 kB
| { | |
| "model": "bn22/Mistral-7B-Instruct-v0.1-sharded", | |
| "data_path": ".", | |
| "project_name": "mistral-7b-cnc-finetuned", | |
| "train_split": "train", | |
| "valid_split": null, | |
| "text_column": "text", | |
| "rejected_text_column": "rejected", | |
| "token": null, | |
| "lr": 0.0002, | |
| "epochs": 1, | |
| "batch_size": 4, | |
| "warmup_ratio": 0.1, | |
| "gradient_accumulation": 1, | |
| "optimizer": "adamw_torch", | |
| "scheduler": "linear", | |
| "weight_decay": 0.0, | |
| "max_grad_norm": 1.0, | |
| "seed": 42, | |
| "add_eos_token": false, | |
| "block_size": -1, | |
| "use_peft": true, | |
| "lora_r": 16, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.05, | |
| "logging_steps": -1, | |
| "evaluation_strategy": "epoch", | |
| "save_total_limit": 1, | |
| "save_strategy": "epoch", | |
| "auto_find_batch_size": false, | |
| "fp16": false, | |
| "push_to_hub": false, | |
| "use_int8": false, | |
| "model_max_length": 1024, | |
| "repo_id": "baebee/mistral-7b-cnc-finetuned", | |
| "use_int4": true, | |
| "trainer": "sft", | |
| "target_modules": "q_proj,v_proj", | |
| "merge_adapter": false, | |
| "username": null, | |
| "use_flash_attention_2": false, | |
| "log": "none", | |
| "disable_gradient_checkpointing": false, | |
| "model_ref": null, | |
| "dpo_beta": 0.1, | |
| "prompt_text_column": "prompt" | |
| } |