Instructions to use sravaniayyagari/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sravaniayyagari/lora_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bitext/Mistral-7B-Mortgage-Loans") model = PeftModel.from_pretrained(base_model, "sravaniayyagari/lora_model") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sravaniayyagari/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 1.8 MB
-
https://huggingface.co/sravaniayyagari/lora_model/resolve/69cc7a5ef9219c329a603d7e4949872b78f2415b/tokenizer.json
- Command line
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hf download hf://sravaniayyagari/lora_model@69cc7a5ef9219c329a603d7e4949872b78f2415b/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sravaniayyagari/lora_model/resolve/69cc7a5ef9219c329a603d7e4949872b78f2415b/tokenizer.json
1.8 MB
File too large to display, you can check the raw version instead.