Feature Extraction
sentence-transformers
Safetensors
English
colqwen2
multi-vector
colbert
late-interaction
Generated from Trainer
dataset_size:3475
loss:MultiVectorMultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use tomaarsen/multivector-colqwen2-v1.0-hf-docqa-energy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tomaarsen/multivector-colqwen2-v1.0-hf-docqa-energy with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/multivector-colqwen2-v1.0-hf-docqa-energy") 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
| { | |
| "image_processor": { | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "Qwen2VLImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "merge_size": 2, | |
| "patch_size": 14, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 602112, | |
| "shortest_edge": 3136 | |
| }, | |
| "temporal_patch_size": 2 | |
| }, | |
| "processor_class": "ColQwen2Processor", | |
| "query_prefix": "Query: ", | |
| "visual_prompt_prefix": "<|im_start|>user\n<|vision_start|><|image_pad|><|vision_end|>Describe the image.<|im_end|><|endoftext|>" | |
| } | |