Instructions to use bane5631/6a567ecd-954b-47cf-9350-bc590838018b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bane5631/6a567ecd-954b-47cf-9350-bc590838018b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M") model = PeftModel.from_pretrained(base_model, "bane5631/6a567ecd-954b-47cf-9350-bc590838018b") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bane5631/6a567ecd-954b-47cf-9350-bc590838018b: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/bane5631/6a567ecd-954b-47cf-9350-bc590838018b/resolve/main/training_args.bin
- Command line
-
hf download hf://bane5631/6a567ecd-954b-47cf-9350-bc590838018b/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bane5631/6a567ecd-954b-47cf-9350-bc590838018b/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 829f2f50099288dc2cc456403859bf2d5eb7148b8fc3213c814145c2f87c2f91
- Size of remote file:
- 6.78 kB
- SHA256:
- 2bbb8a37f9420f77298de288afa3939591eb5bba9af2771f6ff737a4c34239c6
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