Instructions to use askenaz/results_modified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use askenaz/results_modified with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "askenaz/results_modified") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from askenaz/results_modified: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/askenaz/results_modified/resolve/main/training_args.bin
- Command line
-
hf download hf://askenaz/results_modified/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/askenaz/results_modified/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 113d7c8c0f339a6af50a60b5a072bd26501b28dbf4511467089e944e1dc20786
- Size of remote file:
- 4.73 kB
- SHA256:
- dafaa17875a1f618c6da6d10a081f8682e29f30800e9def47edc09f5158656a7
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