Text Classification
Transformers
PyTorch
Safetensors
English
bert
disfluency identification
text-embeddings-inference
Instructions to use 4i-ai/BERT_disfluency_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 4i-ai/BERT_disfluency_cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="4i-ai/BERT_disfluency_cls")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("4i-ai/BERT_disfluency_cls") model = AutoModelForSequenceClassification.from_pretrained("4i-ai/BERT_disfluency_cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 4i-ai/BERT_disfluency_cls: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/4i-ai/BERT_disfluency_cls/resolve/main/training_args.bin
- Command line
-
hf download hf://4i-ai/BERT_disfluency_cls/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/4i-ai/BERT_disfluency_cls/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- 4d2d73af0a58e67d7afadc98f12c40c915713080fdef76653770ae13b3f5266d
- Size of remote file:
- 3.44 kB
- SHA256:
- bc3f728bb954ad04a9a7104f6368ca5eb4dc802140c56db01820de86abb371aa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.