Instructions to use zharry29/intent_snips_wh_id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zharry29/intent_snips_wh_id with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("zharry29/intent_snips_wh_id") model = AutoModelForMultipleChoice.from_pretrained("zharry29/intent_snips_wh_id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from zharry29/intent_snips_wh_id: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/zharry29/intent_snips_wh_id/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://zharry29/intent_snips_wh_id/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/zharry29/intent_snips_wh_id/resolve/main/flax_model.msgpack
1.42 GB
- Xet hash:
- 183d38f3857d33cdee56c0f42a8c9b494c531dcb4156c11a6722d3028cd25e0c
- Size of remote file:
- 1.42 GB
- SHA256:
- 9d6487afbc8dd363aa95d08de964fe17d9fdbfd0fcd5de80c87edd98c9c6ebc9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.