Instructions to use Castial/FinQwen-2.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Castial/FinQwen-2.5b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Castial/FinQwen-2.5b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Castial/FinQwen-2.5b: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Castial/FinQwen-2.5b/resolve/main/tokenizer.json
- Command line
-
hf download hf://Castial/FinQwen-2.5b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Castial/FinQwen-2.5b/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 0c4de4cc81fcfd2a2cd0a65724a6e234342fbde8771ddd8b7a88dea8db367d17
- Size of remote file:
- 11.4 MB
- SHA256:
- 85acc0ed1a93f8b0e6c803b53edf0fe4898ac19a3fff657f21020d280364a0cf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.