Instructions to use nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/GPT4-x-Vicuna-13b-fp16") model = PeftModel.from_pretrained(base_model, "nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d: direct link, hf CLI and curl.
- Browser
- Download file 3.62 MB
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https://huggingface.co/nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d/resolve/main/tokenizer.json
- Command line
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hf download hf://nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/nblinh63/696d40f2-b496-4458-b10d-52b1906fe53d/resolve/main/tokenizer.json
3.62 MB
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