Instructions to use shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03 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, "shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03/resolve/f2cdb31582fe2a4ad8fe0b44aec255d362eba03e/training_args.bin
- Command line
-
hf download hf://shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03@f2cdb31582fe2a4ad8fe0b44aec255d362eba03e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shibajustfor/ca090f5f-b8c0-437a-9443-917c9d145d03/resolve/f2cdb31582fe2a4ad8fe0b44aec255d362eba03e/training_args.bin
6.78 kB
- Xet hash:
- 258dc7554201026ea2280cd14c408b01e09a4d30c2fa635ad53f5b4620f6e4f0
- Size of remote file:
- 6.78 kB
- SHA256:
- fa4540795a0455ce12ed5fcf3e3fd5e5605658d796e341d204b12f99ebcc366a
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