Text Classification
Transformers
PyTorch
Enawené-Nawé
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use ziadA123/trainModel_p1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ziadA123/trainModel_p1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ziadA123/trainModel_p1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ziadA123/trainModel_p1") model = AutoModelForSequenceClassification.from_pretrained("ziadA123/trainModel_p1") - 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 sha256:61fe9193b19a22a2c85356d96c669db46ce3c248aacb541e91a7d4f145863ebd
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size 651399264
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