Instructions to use dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
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https://huggingface.co/dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61/resolve/main/tokenizer.json
- Command line
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hf download hf://dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/dimasik2987/06ab5930-89f9-45c2-951e-9af69b1e5c61/resolve/main/tokenizer.json
3.51 MB
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