Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use racro/sentiment-browser-extension with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use racro/sentiment-browser-extension with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="racro/sentiment-browser-extension")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("racro/sentiment-browser-extension") model = AutoModelForSequenceClassification.from_pretrained("racro/sentiment-browser-extension") - 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 sha256:7c65212d32f3883e7e6443f6ad5632d1fb3a81af971de521e3a89fa87fe04384
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size 267832564
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