Instructions to use sergioalves/9c842882-c751-416a-9522-d4aa4a501dde with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sergioalves/9c842882-c751-416a-9522-d4aa4a501dde with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "sergioalves/9c842882-c751-416a-9522-d4aa4a501dde") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from sergioalves/9c842882-c751-416a-9522-d4aa4a501dde: direct link, hf CLI and curl.
- Browser
- Download file 6.71 kB
-
https://huggingface.co/sergioalves/9c842882-c751-416a-9522-d4aa4a501dde/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://sergioalves/9c842882-c751-416a-9522-d4aa4a501dde/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sergioalves/9c842882-c751-416a-9522-d4aa4a501dde/resolve/main/last-checkpoint/training_args.bin
6.71 kB
- Xet hash:
- 9177f094c25a5641f74bfc323455610c962c890c1fbe3ae2793aa3e358b1e5dc
- Size of remote file:
- 6.71 kB
- SHA256:
- 51985874f445766f7a73046e2a8a9a66f4471e13b4772b4e70be8fbc1f855056
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