Instructions to use Likich/open-coding-mistral7b-single_code-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Likich/open-coding-mistral7b-single_code-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "Likich/open-coding-mistral7b-single_code-qlora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Likich/open-coding-mistral7b-single_code-qlora: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
-
https://huggingface.co/Likich/open-coding-mistral7b-single_code-qlora/resolve/main/tokenizer.json
- Command line
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hf download hf://Likich/open-coding-mistral7b-single_code-qlora/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Likich/open-coding-mistral7b-single_code-qlora/resolve/main/tokenizer.json
3.51 MB
File too large to display, you can check the raw version instead.