Text Generation
PEFT
Safetensors
English
lora
qlora
sft
legal-ai
tax-law
indian-tax
retrieval-augmented-generation
citation-verification
conversational
Instructions to use JayNagose/LLaMa-3.2-tax-basic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JayNagose/LLaMa-3.2-tax-basic with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "JayNagose/LLaMa-3.2-tax-basic") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from JayNagose/LLaMa-3.2-tax-basic: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/JayNagose/LLaMa-3.2-tax-basic/resolve/main/tokenizer.json
- Command line
-
hf download hf://JayNagose/LLaMa-3.2-tax-basic/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/JayNagose/LLaMa-3.2-tax-basic/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- d1764001543899106a3168f0d55a6a527fadce55b617f89242903ae4ace0ef8d
- Size of remote file:
- 17.2 MB
- SHA256:
- 3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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