Instructions to use dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Math-7B-Instruct") model = PeftModel.from_pretrained(base_model, "dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7/resolve/main/tokenizer.json
- Command line
-
hf download hf://dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dimasik2987/ccda8b3d-0118-4a20-8a83-8e1598737df7/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 2e96dd4ae1d2df772ea3bbc942468b6f624624d437352f82360c528a3910b730
- Size of remote file:
- 11.4 MB
- SHA256:
- fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
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