Instructions to use cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-7B") model = PeftModel.from_pretrained(base_model, "cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20: direct link, hf CLI and curl.
- Browser
- Download file 2.78 MB
-
https://huggingface.co/cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20/resolve/main/vocab.json
- Command line
-
hf download hf://cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20/vocab.json
-
curl -L -o vocab.json https://huggingface.co/cimol/0ea943d2-149b-4d41-904a-afbf75ce1a20/resolve/main/vocab.json
2.78 MB
File too large to display, you can check the raw version instead.