Token Classification
Transformers
Safetensors
English
bert
transcript-cleanup
experimental
keep-delete
Instructions to use arach/transcript-cleanup-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arach/transcript-cleanup-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arach/transcript-cleanup-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arach/transcript-cleanup-tiny") model = AutoModelForTokenClassification.from_pretrained("arach/transcript-cleanup-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from arach/transcript-cleanup-tiny: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/arach/transcript-cleanup-tiny/resolve/main/model.safetensors
- Command line
-
hf download hf://arach/transcript-cleanup-tiny/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/arach/transcript-cleanup-tiny/resolve/main/model.safetensors
17.5 MB
- Xet hash:
- 11630a3340720c482b051e3d39d0703e0f95fbc149beb0320b2e283cb5a5abe3
- Size of remote file:
- 17.5 MB
- SHA256:
- 1d7ec6c86525c1d1072a1889b23493df20fc9f59d6c9e0f412e3b5a3fa086208
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.