Instructions to use HYdsl/FinQA-Table-random-DeBERTa-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HYdsl/FinQA-Table-random-DeBERTa-Reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HYdsl/FinQA-Table-random-DeBERTa-Reranker")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HYdsl/FinQA-Table-random-DeBERTa-Reranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download DeBERTa_table_random-table_2e-7/optimizer.pt from HYdsl/FinQA-Table-random-DeBERTa-Reranker: direct link, hf CLI and curl.
- Browser
- Download file 3.48 GB
-
https://huggingface.co/HYdsl/FinQA-Table-random-DeBERTa-Reranker/resolve/main/DeBERTa_table_random-table_2e-7/optimizer.pt
- Command line
-
hf download hf://HYdsl/FinQA-Table-random-DeBERTa-Reranker/DeBERTa_table_random-table_2e-7/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/HYdsl/FinQA-Table-random-DeBERTa-Reranker/resolve/main/DeBERTa_table_random-table_2e-7/optimizer.pt
3.48 GB
- Xet hash:
- 6eaadc826f41f9b082fdb6fde2e29e9bd6e4858802b002a0709b9506686b5b21
- Size of remote file:
- 3.48 GB
- SHA256:
- a0fa4b0e080f5d8f3fa6cb8deb853e396e9f2ea5d8c4cf863bea280f09c423ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.