Polaris_Pro / config.json
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{
"architectures": [
"Qwen3VLForConditionalGeneration"
],
"bio_token_ids": {
"_bio_seq_output_pad": {
"pad": 151687
},
"contact_map": {
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"pad": 151683,
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},
"dna": {
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},
"mol": {
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},
"protein": {
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"pad": 151677,
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},
"rna": {
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"pad": 151671,
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},
"weather": {
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"pad": 151686,
"start": 151684
}
},
"bos_token_id": null,
"dna_config": {
"_name_or_path": "",
"architectures": null,
"chunk_size_feed_forward": 0,
"conv_kernel_size": 7,
"dna_encoder_hidden_size": 512,
"dna_encoder_path": "dna",
"dna_max_seq_length": 2048,
"dna_projector_hidden_size": 2048,
"dna_vocab_size": 8,
"dropout": 0.1,
"dtype": null,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"is_encoder_decoder": false,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"model_type": "qwen3_vl_dna",
"num_attention_heads": 8,
"num_encoder_layers": 8,
"num_latent_tokens": 64,
"output_attentions": false,
"output_hidden_states": false,
"problem_type": null,
"return_dict": true
},
"dtype": "bfloat16",
"eos_token_id": 151645,
"epi_ohem_enable": false,
"epi_ohem_hard_fraction": 0.5,
"epi_ohem_weight": 2.0,
"image_token_id": 151655,
"med_seg_config": {
"cost_bbox": 5.0,
"cost_class": 2.0,
"cost_dice": 5.0,
"cost_giou": 2.0,
"cost_mask": 5.0,
"focal_alpha": 0.25,
"focal_gamma": 2.0,
"freeze_sam3": true,
"freeze_sam3_vision": false,
"loss_w_bbox_giou": 0.5,
"loss_w_bbox_l1": 0.5,
"loss_w_cls": 1.0,
"loss_w_mask_dice": 5.0,
"loss_w_mask_dice_high": 0.0,
"loss_w_mask_focal": 2.0,
"loss_w_mask_semantic": 0.5,
"loss_w_meta_ce": 0.2,
"mask_cost_res": 128,
"mask_h": 576,
"mask_loss_target_res": null,
"mask_w": 576,
"med_query_end_id": null,
"med_query_start_id": null,
"meta_num_classes": 15,
"proj_hidden_mult": 2,
"proj_mlp": true,
"sam3_model_path": null,
"sam3_text_dim": 256,
"system_prompt": "You are a medical imaging assistant specialized in image understanding for segmentation.\nYou will be provided with (1) a medical image and (2) a text query that specifies a target region to segment.\nYour goal is to produce a detailed, clinically plausible description that helps delineate the target region precisely.\nPlease describe:\n 1) The imaging modality/type if it is evident (e.g., CT, MRI, ultrasound, X-ray, endoscopy, dermoscopy, histopathology). If uncertain, explicitly say it is unknown.\n 2) The overall field of view and orientation (e.g., axial/sagittal/coronal for cross-sectional images, or a general view if not applicable).\n 3) The main anatomical structures/organs visible, and for each one provide approximate location using spatial terms. (left/right, superior/inferior, anterior/posterior, central/peripheral) and relative relationships between organs.\n 4) Most importantly, focus on the structure mentioned in the text query: describe its approximate position, boundaries, shape, size, and its appearance (intensity/color, texture, homogeneity, and contrast to surrounding tissues).\n Be concise but detailed, use precise spatial language, and emphasize features helpful for pixel-accurate segmentation.",
"upsample_mask_loss": false,
"use_query_special_tokens": false
},
"med_seg_freeze_qwen": true,
"med_seg_visual_fp32": false,
"modality_configs": {},
"model_type": "qwen3_vl",
"mol_config": {
"_name_or_path": "",
"architectures": null,
"chunk_size_feed_forward": 0,
"dropout": 0.1,
"dtype": null,
"freeze_gnn": true,
"freeze_mol_gnn": true,
"gnn_drop_ratio": 0.0,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"is_encoder_decoder": false,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"model_type": "qwen3_vl_mol",
"mol_decoder_hidden_size": 768,
"mol_decoder_max_seq_length": 512,
"mol_decoder_num_heads": 12,
"mol_decoder_num_layers": 6,
"mol_encoder_hidden_size": 256,
"mol_encoder_path": "mol",
"mol_projector_hidden_size": 1024,
"mol_vocab_size": 226,
"num_gnn_layers": 12,
"num_latent_tokens": 64,
"num_resampler_heads": 8,
"output_attentions": false,
"output_hidden_states": false,
"problem_type": null,
"return_dict": true
},
"pad_token_id": 151643,
"protein_config": {
"_name_or_path": "",
"architectures": null,
"chunk_size_feed_forward": 0,
"conv_kernel_size": 7,
"dropout": 0.1,
"dtype": null,
"esmc_model_name": "esm2_t30_150M_UR50D",
"freeze_backbone": true,
"freeze_esmc": true,
"freeze_protein_backbone": true,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"is_encoder_decoder": false,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"model_type": "qwen3_vl_protein",
"num_attention_heads": 8,
"num_encoder_layers": 12,
"num_latent_tokens": 64,
"num_resampler_layers": 2,
"output_attentions": false,
"output_hidden_states": false,
"problem_type": null,
"protein_backbone_name": "esm2_t30_150M_UR50D",
"protein_convformer_vocab_size": 33,
"protein_encoder_hidden_size": 640,
"protein_encoder_path": "protein",
"protein_max_seq_length": 8192,
"protein_projector_hidden_size": 2560,
"protein_vocab_size": 31,
"return_dict": true,
"use_physicochemical_embed": true
},
"rna_config": {
"_name_or_path": "",
"architectures": null,
"chunk_size_feed_forward": 0,
"conv_kernel_size": 7,
"dropout": 0.1,
"dtype": null,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"is_encoder_decoder": false,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"model_type": "qwen3_vl_rna",
"num_attention_heads": 8,
"num_encoder_layers": 8,
"num_latent_tokens": 64,
"output_attentions": false,
"output_hidden_states": false,
"problem_type": null,
"return_dict": true,
"rna_encoder_hidden_size": 512,
"rna_encoder_path": "rna",
"rna_max_seq_length": 4096,
"rna_projector_hidden_size": 2048,
"rna_vocab_size": 8
},
"text_config": {
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 151643,
"dtype": "bfloat16",
"eos_token_id": 151645,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 12288,
"max_position_embeddings": 262144,
"model_type": "qwen3_vl_text",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"mrope_interleaved": true,
"mrope_section": [
24,
20,
20
],
"rope_theta": 5000000,
"rope_type": "default"
},
"rope_theta": 5000000,
"tie_word_embeddings": false,
"use_cache": true,
"vocab_size": 151936
},
"text_loss_weight": 1.0,
"tie_word_embeddings": false,
"transformers_version": "5.0.0",
"use_cache": false,
"video_token_id": 151656,
"vision_config": {
"deepstack_visual_indexes": [
8,
16,
24
],
"depth": 27,
"dtype": "bfloat16",
"hidden_act": "gelu_pytorch_tanh",
"hidden_size": 1152,
"in_channels": 3,
"initializer_range": 0.02,
"intermediate_size": 4304,
"model_type": "qwen3_vl",
"num_heads": 16,
"num_position_embeddings": 2304,
"out_hidden_size": 4096,
"patch_size": 16,
"spatial_merge_size": 2,
"temporal_patch_size": 2
},
"vision_end_token_id": 151653,
"vision_start_token_id": 151652,
"weather_config": {
"_name_or_path": "",
"architectures": null,
"attn_type": "flash",
"chunk_size_feed_forward": 0,
"const_chans": 6,
"decoder_depth": 12,
"dtype": null,
"embed_freq": 256,
"embed_mode": "add",
"embed_types": [
"step",
"hour",
"doy",
"lead_hour"
],
"encoder_depth": 12,
"ffn_type": "geglu_ffn",
"frame_interval": "6h",
"hidden_size": 2048,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"image_size": [
721,
1440
],
"in_chans": 70,
"in_frames": 1,
"is_encoder_decoder": false,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"lead_hour_scaling": true,
"lower_chans": 0,
"mask_type": "h",
"max_rollout_steps": 200,
"meteo_data_path": null,
"meteo_loss_coef": 1.0,
"meteo_loss_type": "l1_channel",
"meteo_loss_weight": 1.0,
"meteo_out_channels": 70,
"meteo_output_size": [
721,
1440
],
"meteo_token_id": 151655,
"mlp_ratio": 4.0,
"model_type": "qwen3_vl_weather",
"n_kv_heads": null,
"norm_type": "adarms",
"num_heads": 32,
"output_attentions": false,
"output_hidden_states": false,
"patch_size": 6,
"pl_chans": null,
"problem_type": null,
"qwenvl_dim": 4096,
"return_dict": true,
"time_embed_dropout": 0.0,
"upper_chans": 70,
"window_size": 20
}
}