Instructions to use minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-Mistral-7B-DPO") model = PeftModel.from_pretrained(base_model, "minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
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https://huggingface.co/minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99/resolve/main/tokenizer.json
- Command line
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hf download hf://minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/minhnguyennnnnn/556570cf-ce78-4bea-a280-0c31a84e0e99/resolve/main/tokenizer.json
3.51 MB
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