Instructions to use kaliansh/pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaliansh/pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kaliansh/pos")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kaliansh/pos") model = AutoModelForTokenClassification.from_pretrained("kaliansh/pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from kaliansh/pos: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/kaliansh/pos/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://kaliansh/pos/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/kaliansh/pos/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- 418d550f6ce940746b5d1d73907a6b3b46d3e56ae557bd34ffc23438d4d9c177
- Size of remote file:
- 436 MB
- SHA256:
- d33433f5cd9271b72ccbd0e7ca141ef07c91c3c6625ea4cfae434fec5585a8df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.