Text Classification
Transformers
Safetensors
English
bert
sentiment-analysis
manav
ManavDhayeCoder/sentiment-bert
ManavDhaye
text-embeddings-inference
Instructions to use ManavDhayeCoder/sentiment-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManavDhayeCoder/sentiment-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ManavDhayeCoder/sentiment-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ManavDhayeCoder/sentiment-bert") model = AutoModelForSequenceClassification.from_pretrained("ManavDhayeCoder/sentiment-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7df82bfcb459be6c349c831f36d737358cae3280cda7be46ce988993f49ca44b
- Size of remote file:
- 438 MB
- SHA256:
- 9de3877d263cc0135bae68573ba4c9481406803ed9d5108194511509ee357ec9
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