Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Tirendaz/my_distilbert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tirendaz/my_distilbert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tirendaz/my_distilbert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tirendaz/my_distilbert_model") model = AutoModelForSequenceClassification.from_pretrained("Tirendaz/my_distilbert_model") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#5
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:cab49093717c872db1e5cb677ea9642ee9c7297f2f1b22dd31a4602e946d7c01
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size 267832560
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