Instructions to use abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("echarlaix/tiny-random-mistral") model = PeftModel.from_pretrained(base_model, "abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a: direct link, hf CLI and curl.
- Browser
- Download file 114 kB
-
https://huggingface.co/abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a/resolve/main/adapter_model.safetensors
114 kB
- Xet hash:
- c2995e8edc6d5652b400baea6d53e86c1baa4d04a8926aeede5223232abfc82e
- Size of remote file:
- 114 kB
- SHA256:
- 91f3f5367722895174de5519e9df05cd73c324ff4623566e7480dae735438794
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