Feature Extraction
Transformers
Safetensors
English
qwen3_vl
video-retrieval
multi-vector
late-interaction
colbert
index-compression
attention-guided-clustering
text-to-video
Instructions to use hltcoe/AGC_qwen3-vl_msrvtt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hltcoe/AGC_qwen3-vl_msrvtt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hltcoe/AGC_qwen3-vl_msrvtt")# Load model directly from transformers import AutoProcessor, Qwen3ForEmbedding processor = AutoProcessor.from_pretrained("hltcoe/AGC_qwen3-vl_msrvtt") model = Qwen3ForEmbedding.from_pretrained("hltcoe/AGC_qwen3-vl_msrvtt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 261cd3afa1b4419650d7ff5cf2296047a8581f84b584ab393c5daaf3ba22d3d4
- Size of remote file:
- 4.99 GB
- SHA256:
- 681de333cc9297619ead1f8df24e8b15cbe5c760ffc9e256693072ba483facff
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