Instructions to use JadwalAlmaa/gemma300_dist with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use JadwalAlmaa/gemma300_dist with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("JadwalAlmaa/gemma300_dist") - sentence-transformers
How to use JadwalAlmaa/gemma300_dist with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JadwalAlmaa/gemma300_dist") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1eba719cef5c1c9ebeaed63c0d591a78fecab5a15624c5c4fa632e6814dd90c
- Size of remote file:
- 13.4 MB
- SHA256:
- 4d12a49846fb9bf578218d05d63424b24d252d4348f8e6b5ff18a5b48a7bff6f
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