Instructions to use Freddthink/gemma-2-2b-it-summarization-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Freddthink/gemma-2-2b-it-summarization-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "Freddthink/gemma-2-2b-it-summarization-lora") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from Freddthink/gemma-2-2b-it-summarization-lora: direct link, hf CLI and curl.
- Browser
- Download file 187 Bytes
-
https://huggingface.co/Freddthink/gemma-2-2b-it-summarization-lora/resolve/main/generation_config.json
- Command line
-
hf download hf://Freddthink/gemma-2-2b-it-summarization-lora/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Freddthink/gemma-2-2b-it-summarization-lora/resolve/main/generation_config.json
187 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 2, | |
| "cache_implementation": "hybrid", | |
| "eos_token_id": [ | |
| 1, | |
| 107 | |
| ], | |
| "pad_token_id": 0, | |
| "transformers_version": "4.46.3" | |
| } | |