Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use federicopascual/finetuned-sentiment-analysis-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use federicopascual/finetuned-sentiment-analysis-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="federicopascual/finetuned-sentiment-analysis-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("federicopascual/finetuned-sentiment-analysis-model") model = AutoModelForSequenceClassification.from_pretrained("federicopascual/finetuned-sentiment-analysis-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7243c881719c9e6785e448db88b8302639495f85e3414e5474582818bd107215
- Size of remote file:
- 2.99 kB
- SHA256:
- f6230329fbbeef748db61203083e3b77e1f903ca66a0dd3bf29c36193d2ae168
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