Instructions to use gotzmann/1OV77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gotzmann/1OV77 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "gotzmann/1OV77") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-4500/tokenizer.json from gotzmann/1OV77: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/gotzmann/1OV77/resolve/main/checkpoint-4500/tokenizer.json
- Command line
-
hf download hf://gotzmann/1OV77/checkpoint-4500/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/gotzmann/1OV77/resolve/main/checkpoint-4500/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.