Image-Text-to-Text
Safetensors
ColPali
sentence-transformers
sauerkrautlm-colpali
mistral3
document-retrieval
vision-language-model
multi-vector
late-interaction
visual-retrieval
ministral
pixtral
mistral
mteb
vidore
conversational
Instructions to use VAGOsolutions/SauerkrautLM-ColMinistral3-3b-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use VAGOsolutions/SauerkrautLM-ColMinistral3-3b-v0.1 with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- sentence-transformers
How to use VAGOsolutions/SauerkrautLM-ColMinistral3-3b-v0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VAGOsolutions/SauerkrautLM-ColMinistral3-3b-v0.1") 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
| { | |
| "architectures": [ | |
| "ColMinistral3" | |
| ], | |
| "dtype": "bfloat16", | |
| "image_token_index": 10, | |
| "model_type": "mistral3", | |
| "multimodal_projector_bias": false, | |
| "projector_hidden_act": "gelu", | |
| "spatial_merge_size": 2, | |
| "text_config": { | |
| "attention_dropout": 0.0, | |
| "dtype": "bfloat16", | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 3072, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 9216, | |
| "max_position_embeddings": 262144, | |
| "model_type": "ministral3", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 26, | |
| "num_key_value_heads": 8, | |
| "rms_norm_eps": 1e-05, | |
| "rope_parameters": { | |
| "beta_fast": 32.0, | |
| "beta_slow": 1.0, | |
| "factor": 16.0, | |
| "llama_4_scaling_beta": 0.1, | |
| "mscale": 1.0, | |
| "mscale_all_dim": 1.0, | |
| "original_max_position_embeddings": 16384, | |
| "rope_theta": 1000000.0, | |
| "rope_type": "yarn", | |
| "type": "yarn" | |
| }, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "use_cache": true, | |
| "vocab_size": 131072 | |
| }, | |
| "transformers_version": "5.0.0rc0", | |
| "vision_config": { | |
| "attention_dropout": 0.0, | |
| "dtype": "bfloat16", | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 1024, | |
| "image_size": 1540, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "model_type": "pixtral", | |
| "num_attention_heads": 16, | |
| "num_channels": 3, | |
| "num_hidden_layers": 24, | |
| "patch_size": 14, | |
| "rope_parameters": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "vision_feature_layer": -1, | |
| "base_model": "mistralai/Ministral-3-3B-Reasoning-2512", | |
| "dim": 128, | |
| "mask_non_image_embeddings": false, | |
| "_name_or_path": "VAGOsolutions/SauerkrautLM-ColMinistral3-3b-v0.1" | |
| } |