Instructions to use infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/tokenizer.json from infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
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https://huggingface.co/infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06/resolve/main/last-checkpoint/tokenizer.json
- Command line
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hf download hf://infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06/last-checkpoint/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/infogep/d6a22042-e535-4141-afea-4ebdbd7f7f06/resolve/main/last-checkpoint/tokenizer.json
3.51 MB
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