Instructions to use thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenBuddy/openbuddy-llama2-13b-v8.1-fp16") model = PeftModel.from_pretrained(base_model, "thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc/resolve/main/training_args.bin
- Command line
-
hf download hf://thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thakkkkkk/7e3633ce-fa8c-4831-b385-29873c509fdc/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 60d98e220bdcc1361da4d1f9e8775b1a60e2fc1c21e0cfef0be6cfc54898a480
- Size of remote file:
- 6.78 kB
- SHA256:
- a56bc1fda0dfbf7f1fc20663d57562cd4f6380264fd85e74e8b6602d9d8e0865
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