Instructions to use error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") model = PeftModel.from_pretrained(base_model, "error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156: direct link, hf CLI and curl.
- Browser
- Download file 3.86 MB
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https://huggingface.co/error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156/resolve/01a38c36b4f7e3a56abbf6d2bb37476db0924b9e/tokenizer.json
- Command line
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hf download hf://error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156@01a38c36b4f7e3a56abbf6d2bb37476db0924b9e/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156/resolve/01a38c36b4f7e3a56abbf6d2bb37476db0924b9e/tokenizer.json
3.86 MB
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