Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use gokuls/BERT-tiny-Massive-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gokuls/BERT-tiny-Massive-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gokuls/BERT-tiny-Massive-intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gokuls/BERT-tiny-Massive-intent") model = AutoModelForSequenceClassification.from_pretrained("gokuls/BERT-tiny-Massive-intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gokuls/BERT-tiny-Massive-intent: direct link, hf CLI and curl.
- Browser
- Download file 17.6 MB
-
https://huggingface.co/gokuls/BERT-tiny-Massive-intent/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gokuls/BERT-tiny-Massive-intent/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gokuls/BERT-tiny-Massive-intent/resolve/main/pytorch_model.bin
17.6 MB
- Xet hash:
- 07d4107c1ac4fcea2fbf2e90247854a3a5069543f8d7df4b93efa11fdf6762fc
- Size of remote file:
- 17.6 MB
- SHA256:
- 1f65ddcc456deae69d4a5f96fec0a419564c4ae7d41cb5e49a001353c9b4a13f
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