Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use gayatrividhate/SetFit_sentiment_analysis_ep20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gayatrividhate/SetFit_sentiment_analysis_ep20 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gayatrividhate/SetFit_sentiment_analysis_ep20") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use gayatrividhate/SetFit_sentiment_analysis_ep20 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gayatrividhate/SetFit_sentiment_analysis_ep20") model = AutoModel.from_pretrained("gayatrividhate/SetFit_sentiment_analysis_ep20") - Notebooks
- Google Colab
- Kaggle
File size: 122 Bytes
784077a | 1 2 3 4 5 6 7 | {
"__version__": {
"sentence_transformers": "2.0.0",
"transformers": "4.7.0",
"pytorch": "1.9.0+cu102"
}
} |