Instructions to use Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v0.6") model = PeftModel.from_pretrained(base_model, "Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54: direct link, hf CLI and curl.
- Browser
- Download file 101 MB
-
https://huggingface.co/Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/Rodo-Sami/c5c8fa44-97ca-4d79-a3cd-daca64cd9f54/resolve/main/adapter_model.safetensors
101 MB
- Xet hash:
- fdf3b7dba96a01a9badfb7bd3fe9bf2e74258fdcf7e2c2b2b8063a2f401c82f9
- Size of remote file:
- 101 MB
- SHA256:
- d6e217e69c74543151fdd06a0b25b701831c0587f803ee1e31cf04c2d69e2c1d
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