Instructions to use tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951 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, "tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951: direct link, hf CLI and curl.
- Browser
- Download file 120 kB
-
https://huggingface.co/tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951/resolve/main/adapter_model.bin
- Command line
-
hf download hf://tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/tuantmdev/05b3a41e-7187-4f77-bfcc-d205d0a2e951/resolve/main/adapter_model.bin
120 kB
- Xet hash:
- 2a6bbc2618f75f8da5d06510eb9fb135d5907d4155a14045f636aabf907e7cfd
- Size of remote file:
- 120 kB
- SHA256:
- f2ab85e8abd8833c40feda2ccd14c5f6f68e9f072c55330d7e0b28ae862cb2d2
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