Instructions to use bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522/resolve/main/training_args.bin
- Command line
-
hf download hf://bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bane5631/aad541df-5aeb-414a-8bef-2f54a78e6522/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- a1bba73e16a463755ea150d63cd68c205d113884cc4f3134734fae1cc95fbd4f
- Size of remote file:
- 6.78 kB
- SHA256:
- 2b19d29839b19e0d223eccc8d9edfa4511a047e643568b55f85d2d7dd591ed6c
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