Instructions to use Yhyu13/LMCocktail-10.7B-v1-function-calling-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Yhyu13/LMCocktail-10.7B-v1-function-calling-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Yhyu13/LMCocktail-10.7B-v1") model = PeftModel.from_pretrained(base_model, "Yhyu13/LMCocktail-10.7B-v1-function-calling-lora") - Notebooks
- Google Colab
- Kaggle
Download Predict_20/predict_results.json from Yhyu13/LMCocktail-10.7B-v1-function-calling-lora: direct link, hf CLI and curl.
- Browser
- Download file 256 Bytes
-
https://huggingface.co/Yhyu13/LMCocktail-10.7B-v1-function-calling-lora/resolve/main/Predict_20/predict_results.json
- Command line
-
hf download hf://Yhyu13/LMCocktail-10.7B-v1-function-calling-lora/Predict_20/predict_results.json
-
curl -L -o predict_results.json https://huggingface.co/Yhyu13/LMCocktail-10.7B-v1-function-calling-lora/resolve/main/Predict_20/predict_results.json
256 Bytes
| { | |
| "predict_bleu-4": 84.02507, | |
| "predict_rouge-1": 88.655265, | |
| "predict_rouge-2": 80.23742000000001, | |
| "predict_rouge-l": 86.469845, | |
| "predict_runtime": 37.4743, | |
| "predict_samples_per_second": 0.534, | |
| "predict_steps_per_second": 0.534 | |
| } |