Text Classification
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use nickmuchi/setfit-finetuned-financial-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nickmuchi/setfit-finetuned-financial-text with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nickmuchi/setfit-finetuned-financial-text") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use nickmuchi/setfit-finetuned-financial-text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nickmuchi/setfit-finetuned-financial-text")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nickmuchi/setfit-finetuned-financial-text") model = AutoModel.from_pretrained("nickmuchi/setfit-finetuned-financial-text") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2 opened over 1 year ago
by
SFconvertbot
Inference Error
#1 opened over 3 years ago
by
nickmuchi