Feature Extraction
Transformers
Safetensors
sentence-transformers
multilingual
embedding_gemma2
embedding
multimodal-embedding
multimodal
vision
audio
video
image-feature-extraction
audio-feature-extraction
video-feature-extraction
sentence-similarity
Instructions to use PulsePoint/Flex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PulsePoint/Flex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="PulsePoint/Flex")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("PulsePoint/Flex") model = AutoModel.from_pretrained("PulsePoint/Flex", device_map="auto") - sentence-transformers
How to use PulsePoint/Flex with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PulsePoint/Flex") 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
File size: 1,565 Bytes
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"__version__": {
"pytorch": "2.14.0+cu130",
"sentence_transformers": "6.1.0",
"transformers": "5.18.0.dev0"
},
"default_prompt_name": null,
"model_type": "SentenceTransformer",
"prompts": {
"BitextMining": "task: search result | query: ",
"Classification": "task: classification | query: ",
"Clustering": "task: clustering | query: ",
"CodeRetrieval": "task: code retrieval | query: ",
"Document": "title: none | text: ",
"FactChecking": "task: fact checking | query: ",
"InstructionRetrieval": "task: code retrieval | query: ",
"MultilabelClassification": "task: classification | query: ",
"PairClassification": "task: sentence similarity | query: ",
"QuestionAnswering": "task: question answering | query: ",
"Reranking": "task: search result | query: ",
"Retrieval": "task: search result | query: ",
"Retrieval-document": "title: none | text: ",
"Retrieval-query": "task: search result | query: ",
"STS": "task: sentence similarity | query: ",
"SearchQuery": "task: search result | query: ",
"SentenceSimilarity": "task: sentence similarity | query: ",
"Summarization": "task: sentence similarity | query: ",
"document": "title: none | text: ",
"query": "task: search result | query: "
},
"requirements": {
"sentence-transformers": {
"reason": "Older versions ignore the order of multimodal dict inputs and cannot put several images or texts into a single embedding.",
"specifier": ">=6.1.0"
}
},
"similarity_fn_name": "cosine"
}
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