Instructions to use minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/zephyr-sft") model = PeftModel.from_pretrained(base_model, "minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc/resolve/main/adapter_model.bin
- Command line
-
hf download hf://minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/minhnguyennnnnn/71d6b5ce-210d-446d-a9bf-288b5a91d3cc/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- 9a4548dcedb85e76b9045bcf10551df2c7337deef202cc94a94b5acdad4491fc
- Size of remote file:
- 84 MB
- SHA256:
- dc9fc193bb3bbfdf89f69766d0213f3d511bbae87d4177d950adb03f847c46df
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