Instructions to use akashmaggon/llama-functioncalling-salesforce-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akashmaggon/llama-functioncalling-salesforce-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("akashmaggon/llama-functioncalling-salesforce-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from akashmaggon/llama-functioncalling-salesforce-2: direct link, hf CLI and curl.
- Browser
- Download file 5.62 kB
-
https://huggingface.co/akashmaggon/llama-functioncalling-salesforce-2/resolve/main/training_args.bin
- Command line
-
hf download hf://akashmaggon/llama-functioncalling-salesforce-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/akashmaggon/llama-functioncalling-salesforce-2/resolve/main/training_args.bin
5.62 kB
- Xet hash:
- a03bc69715aadbd1ab301edf66017b345fa5db3b2cea7d2b5ba8c3c4489fa0f7
- Size of remote file:
- 5.62 kB
- SHA256:
- 8f29e2a6dfe7974896a871ac3457d4fe2ad12689dfd59c22a9185423601614a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.