Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use vdivya/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vdivya/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vdivya/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vdivya/dummy-model") model = AutoModelForSequenceClassification.from_pretrained("vdivya/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from vdivya/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/vdivya/dummy-model/resolve/main/tf_model.h5
- Command line
-
hf download hf://vdivya/dummy-model/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/vdivya/dummy-model/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 67b4bc676d80445fe1bc13e431dd40db06d78893f0c8d04e0c78842823ca4d80
- Size of remote file:
- 438 MB
- SHA256:
- e9943804b3a1db4384a326d281399f1e8a58cdde6d641d851e5d3f864ea313fe
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