Instructions to use agilan1102/LLama_financial_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use agilan1102/LLama_financial_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3.2-3b-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "agilan1102/LLama_financial_model") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from agilan1102/LLama_financial_model: direct link, hf CLI and curl.
- Browser
- Download file 18.5 MB
-
https://huggingface.co/agilan1102/LLama_financial_model/resolve/main/tokenizer.json
- Command line
-
hf download hf://agilan1102/LLama_financial_model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/agilan1102/LLama_financial_model/resolve/main/tokenizer.json
18.5 MB
- Xet hash:
- 17756870b8e1af430c83025d313fb88c509292291e5fcd46d1fb9f3ab22884d4
- Size of remote file:
- 18.5 MB
- SHA256:
- acbb26b8d3121ebf65c2c9a09726d7ad0d16471b75d45cac92285d170bb4ae86
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