Image Segmentation
Transformers
Safetensors
English
calico
text-generation
computer-vision
semantic-segmentation
co-segmentation
part-segmentation
multi-image-reasoning
vision-language
Instructions to use PLAN-Lab/CALICO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PLAN-Lab/CALICO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="PLAN-Lab/CALICO")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("PLAN-Lab/CALICO", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,624 Bytes
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"_name_or_path": "PLAN-Lab/CALICO",
"architectures": [
"CALICOForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"auto_initialize_adaptors": true,
"auto_initialize_qformer": true,
"bbox_token_idx": 32002,
"bos_token_id": 1,
"dino_hidden_size": 768,
"dino_model_name": "dinov2_vitb14_reg",
"eos_token_id": 2,
"global_image_size": 224,
"grounding_encoder": "sam_vit_h",
"grounding_image_size": 1024,
"hidden_act": "silu",
"hidden_size": 4096,
"image_aspect": "square",
"image_aspect_ratio": "square",
"initializer_range": 0.02,
"intermediate_size": 11008,
"layer_type": "linear",
"max_position_embeddings": 4096,
"mlp_bias": false,
"mm_projector_type": "linear",
"model_type": "calico",
"num_attention_heads": 32,
"num_attn_heads": 8,
"num_hidden_layers": 32,
"num_key_value_heads": 32,
"num_level_reg_features": 4,
"num_query_tokens": 32,
"out_dim": 256,
"pad_token_id": 0,
"pretraining_tp": 1,
"q_former_model": "",
"qformer_hidden_size": 768,
"qformer_vision_encoder": "eva_clip_g",
"qformer_vision_width": 1408,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 10000.0,
"seg_image_tokens": [
[
32004,
313,
2382,
29896
],
[
32004,
313,
2382,
29906
]
],
"seg_token_idx": 32004,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"train_mask_decoder": true,
"transformers_version": "4.42.3",
"update_layers": [
11,
22
],
"use_cache": false,
"use_mm_proj": true,
"vocab_size": 32007,
"with_region": true
}
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