Feature Extraction
Transformers
Safetensors
English
qwen2_5_omni_thinker
video-retrieval
multi-vector
late-interaction
colbert
index-compression
attention-guided-clustering
text-to-video
audiovisual
Instructions to use hltcoe/AGC_qwen2.5-omni_multivent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hltcoe/AGC_qwen2.5-omni_multivent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hltcoe/AGC_qwen2.5-omni_multivent")# Load model directly from transformers import AutoTokenizer, Qwen2_5OmniForEmbedding tokenizer = AutoTokenizer.from_pretrained("hltcoe/AGC_qwen2.5-omni_multivent") model = Qwen2_5OmniForEmbedding.from_pretrained("hltcoe/AGC_qwen2.5-omni_multivent") - Notebooks
- Google Colab
- Kaggle
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