Instructions to use kobesar/FinGPT-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kobesar/FinGPT-llama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("base_models/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "kobesar/FinGPT-llama") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from kobesar/FinGPT-llama: direct link, hf CLI and curl.
- Browser
- Download file 888 Bytes
-
https://huggingface.co/kobesar/FinGPT-llama/resolve/main/adapter_model.bin
- Command line
-
hf download hf://kobesar/FinGPT-llama/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/kobesar/FinGPT-llama/resolve/main/adapter_model.bin
888 Bytes
- Xet hash:
- b5b61aea3ceffa1f57a43343abeeca48180d81010b71c197bc0d40f6198a3fbe
- Size of remote file:
- 888 Bytes
- SHA256:
- 7eaa51169fb5f5f33b328f26090dcd19a47bde0a9efe64e78856dbbe04a07e7a
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