Instructions to use minishlab/M2V_base_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use minishlab/M2V_base_output with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("minishlab/M2V_base_output") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - sentence-transformers
How to use minishlab/M2V_base_output with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("minishlab/M2V_base_output") 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
Download model.safetensors from minishlab/M2V_base_output: direct link, hf CLI and curl.
- Browser
- Download file 30.2 MB
-
https://huggingface.co/minishlab/M2V_base_output/resolve/main/model.safetensors
- Command line
-
hf download hf://minishlab/M2V_base_output/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/minishlab/M2V_base_output/resolve/main/model.safetensors
30.2 MB
- Xet hash:
- 4a65e397c6193e3a678e7d683d8220ad96ca7c4528e9b84b3a90e1583a75ba9c
- Size of remote file:
- 30.2 MB
- SHA256:
- 7b92697b5376a9416a4c761c3a193ce536b8a178ae52c5cf52b0af3266b73b3f
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