Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use sakgoyal/NLP_HW1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sakgoyal/NLP_HW1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sakgoyal/NLP_HW1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sakgoyal/NLP_HW1") model = AutoModelForSequenceClassification.from_pretrained("sakgoyal/NLP_HW1") - 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 sha256:58f58e1d35ebde5d8bcb70e2c4289286ea8f1a17b6353de0b7b84b8455ae0e23
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size 267832560
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