Instructions to use pranavGenAI/ESG_RFP_Query with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pranavGenAI/ESG_RFP_Query with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pranavGenAI/ESG_RFP_Query", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from pranavGenAI/ESG_RFP_Query: direct link, hf CLI and curl.
- Browser
- Download file 8.4 MB
-
https://huggingface.co/pranavGenAI/ESG_RFP_Query/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://pranavGenAI/ESG_RFP_Query/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/pranavGenAI/ESG_RFP_Query/resolve/main/adapter_model.safetensors
8.4 MB
- Xet hash:
- 4ad6adbdddf31ce991942d8241f0647ac1747da238c7bdf6ab3b226fac4dd3a4
- Size of remote file:
- 8.4 MB
- SHA256:
- c63d467560c8f7fa998bc71eb30af2b472fa844f0e1c6f00e45b7aa7962f5aa3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.