Feature Extraction
Transformers
Safetensors
sentence-transformers
Chinese
English
qwen3_5
image-text-to-text
multimodal-embedding
text-embedding
image-embedding
video-embedding
mrl
custom_code
Instructions to use tencent/WeMM-Embedding-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/WeMM-Embedding-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tencent/WeMM-Embedding-2B", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("tencent/WeMM-Embedding-2B", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("tencent/WeMM-Embedding-2B", trust_remote_code=True, device_map="auto") - sentence-transformers
How to use tencent/WeMM-Embedding-2B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tencent/WeMM-Embedding-2B", 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
File size: 950 Bytes
2db4e30 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | {
"transformer_task": "feature-extraction",
"modality_config": {
"text": {
"method": "embedding",
"method_output_name": null
},
"image": {
"method": "embedding",
"method_output_name": null
},
"video": {
"method": "embedding",
"method_output_name": null
},
"image+text": {
"method": "embedding",
"method_output_name": null
},
"text+video": {
"method": "embedding",
"method_output_name": null
},
"message": {
"method": "embedding",
"method_output_name": null,
"format": "structured"
}
},
"module_output_name": "sentence_embedding",
"processing_kwargs": {
"chat_template": {
"chat_template": "sentence_transformers"
}
},
"unpad_inputs": false
}
|