Instructions to use abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d/resolve/main/tokenizer.json
- Command line
-
hf download hf://abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/abaddon182/6a2dfe2e-2f7a-4197-bbe4-e7c8541ccf6d/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 31d19fffde1c78260dd5b32b98e51dd8adefae216e6eefbcb299f56f4b977337
- Size of remote file:
- 11.4 MB
- SHA256:
- bcfe42da0a4497e8b2b172c1f9f4ec423a46dc12907f4349c55025f670422ba9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.