Instructions to use shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3") model = PeftModel.from_pretrained(base_model, "shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76: direct link, hf CLI and curl.
- Browser
- Download file 3.67 MB
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https://huggingface.co/shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76/resolve/main/tokenizer.json
- Command line
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hf download hf://shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/shibajustfor/a761343e-ba96-419e-b12f-d25922b7ca76/resolve/main/tokenizer.json
3.67 MB
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