Instructions to use quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d/resolve/main/training_args.bin
- Command line
-
hf download hf://quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/quannh197/911ee87c-0694-45d2-a09f-f16a4dc0689d/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 0910afe9818e1dccb524af5b9037a124aa4562ad446d184f6385d68c848738aa
- Size of remote file:
- 6.78 kB
- SHA256:
- 4b021da3b7332d72d8faee47cc85eda1ddc297b76d05b5021a7eb861eb350128
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