Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use danlupu/sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danlupu/sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danlupu/sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danlupu/sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("danlupu/sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e7f62d9433e6b0ff409b156d35e5563161e0bf67f39d4bde72580dcfc96d5b9
- Size of remote file:
- 3.25 kB
- SHA256:
- 92e23ffb32af2095c53b8fc3bc99229b3f4279001198e89fc85e6176f027d5ec
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