Text Classification
Transformers
PyTorch
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use markroot/my-test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markroot/my-test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="markroot/my-test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("markroot/my-test-model") model = AutoModelForSequenceClassification.from_pretrained("markroot/my-test-model") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d457d6873d33853fad4922e6de38278c47973d2512b5fe8a065f085ea2439007
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size 433284180
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