Instructions to use nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c: direct link, hf CLI and curl.
- Browser
- Download file 17.6 MB
-
https://huggingface.co/nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/nhungphammmmm/3a797b6c-4c52-4ff7-a05b-9a2b9ba5807c/resolve/main/adapter_model.safetensors
17.6 MB
- Xet hash:
- df5e57c6b8cec373759aa40e8366ee037f5f5790b627b03608fe8df607396c71
- Size of remote file:
- 17.6 MB
- SHA256:
- 488798b4455e2399f38530c679f5679c1f67444b2bf5b2dd010eb4af2a2b47e1
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