Feature Extraction
Transformers
PyTorch
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use omarelsayeed/Classfier_V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarelsayeed/Classfier_V0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="omarelsayeed/Classfier_V0")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("omarelsayeed/Classfier_V0") model = AutoModel.from_pretrained("omarelsayeed/Classfier_V0") - 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 sha256:1a9cc950c3045f9ea29a41fc8de70296b9e312a90f9be3d1637b04a308e33b1c
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size 437951328
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