Text Generation
PEFT
Safetensors
lora
qlora
mistral
json
structured-output
customer-support
conversational
Instructions to use aashnakunk/mistral-7b-json-support with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aashnakunk/mistral-7b-json-support with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3") model = PeftModel.from_pretrained(base_model, "aashnakunk/mistral-7b-json-support") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from aashnakunk/mistral-7b-json-support: direct link, hf CLI and curl.
- Browser
- Download file 3.67 MB
-
https://huggingface.co/aashnakunk/mistral-7b-json-support/resolve/main/tokenizer.json
- Command line
-
hf download hf://aashnakunk/mistral-7b-json-support/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/aashnakunk/mistral-7b-json-support/resolve/main/tokenizer.json
3.67 MB
File too large to display, you can check the raw version instead.