Zero-Shot Image Classification
sentence-transformers
Safetensors
Sinhala
siglip
trimmed
🇪🇺 Region: EU
Instructions to use alphaedge-ai/siglip2-so400m-patch16-512-sin-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/siglip2-so400m-patch16-512-sin-16384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/siglip2-so400m-patch16-512-sin-16384") 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
Trimmed SigLIP2 text vocab for Sinhala (SP: 16384, ext: 0)
Browse files- config.json +6 -1
- model.safetensors +3 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
config.json
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{
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"initializer_factor": 1.0,
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"model_type": "siglip",
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"text_config": {
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"projection_size": 1152,
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"vocab_size": 16384
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},
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"
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"vision_config": {
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"hidden_size": 1152,
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"image_size": 512,
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{
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"_name_or_path": "google/siglip2-so400m-patch16-512",
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"architectures": [
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"SiglipModel"
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],
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"initializer_factor": 1.0,
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"model_type": "siglip",
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"text_config": {
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"projection_size": 1152,
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"vocab_size": 16384
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},
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"torch_dtype": "float32",
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"transformers_version": "4.46.3",
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"vision_config": {
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"hidden_size": 1152,
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"image_size": 512,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ebc6992851064bebed3521726e75ab49614ac88c11f987999f131404be9b71a0
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size 3442180840
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tokenizer.json
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
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size 4241003
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tokenizer_config.json
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