Sentence Similarity
sentence-transformers
PyTorch
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use ManuelaJeyaraj/few_shot_learner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ManuelaJeyaraj/few_shot_learner with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ManuelaJeyaraj/few_shot_learner") 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 ManuelaJeyaraj/few_shot_learner with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ManuelaJeyaraj/few_shot_learner") model = AutoModel.from_pretrained("ManuelaJeyaraj/few_shot_learner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 742f821625b1b7411a371fab6e88479d551c1b9563b787eb519fea960483f4e2
- Size of remote file:
- 438 MB
- SHA256:
- a44010801857aae395437a9fbc463c938fc8e93ec0ca669a3e93296f685946a6
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