Text Classification
sentence-transformers
Safetensors
falcon
ssmits/Falcon2-5.5B-multilingual
custom_code
Instructions to use ssmits/Falcon2-5.5B-multilingual-embed-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ssmits/Falcon2-5.5B-multilingual-embed-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ssmits/Falcon2-5.5B-multilingual-embed-base", trust_remote_code=True) 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
Update config.json
Browse files- config.json +1 -1
config.json
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"activation": "gelu",
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"alibi": false,
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"architectures": [
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"
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"attention_dropout": 0.0,
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"auto_map": {
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"activation": "gelu",
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"alibi": false,
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"architectures": [
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"FalconModel"
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],
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"attention_dropout": 0.0,
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"auto_map": {
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