Instructions to use dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/resolve/main/tokenizer.json
- Command line
-
hf download hf://dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- a2251c6bff2c6c00b2fb78308145dd8b18dab1926ac9430862919148bd324ccf
- Size of remote file:
- 17.2 MB
- SHA256:
- 2539802b4016767e5475c0fa774895f4c33683f7c2ed9df643a61279e9ef1bd2
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