Feature Extraction
Transformers
Safetensors
English
lessvit
hyperspectral
remote-sensing
geospatial
vision-transformer
custom_code
Instructions to use GFM-Bench/LESSViT-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GFM-Bench/LESSViT-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GFM-Bench/LESSViT-Base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GFM-Bench/LESSViT-Base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,283 Bytes
586325c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | {
"architectures": [
"LESSViTModel"
],
"attention_radius": 640,
"attn_drop": 0.1,
"attn_type": "less",
"channel_dim": 24,
"channel_dropout": null,
"channel_embed_dims_per_head": 2,
"channel_mask_ratio": 0.0,
"decoder_channel_dim": 64,
"decoder_depth": 8,
"decoder_embed_dim": 512,
"decoder_num_heads": 16,
"decoder_out_chans": 1,
"decoder_rope_channel_split_dim": 256,
"decoder_rope_spatial_split_dim": 256,
"decoder_spatial_dim": 128,
"depth": 12,
"drop_path_rate": 0.1,
"drop_path_uniform": false,
"embed_dim": 768,
"fusion_init_scale": 1.0,
"init_values": 1.0,
"mask_ratio": 0.0,
"mlp_ratio": 4.0,
"model_type": "lessvit",
"norm_pix_loss": true,
"num_heads": 12,
"num_tokens": 1,
"patch_size": 16,
"pos_chan_embed_residual": true,
"pretrain": false,
"proj_drop": 0.1,
"qk_norm": false,
"qkv_bias": true,
"rank": 1,
"return_dict": true,
"rope_channel_split_dim": 384,
"rope_embed_base": 100.0,
"rope_spatial_split_dim": 384,
"spatial_dim": 384,
"torch_dtype": "float32",
"transformers_version": "4.53.3",
"use_perception_field_mask": true,
"use_rope_embed": true,
"auto_map": {
"AutoConfig": "modeling_lessvit.LESSViTConfig",
"AutoModel": "modeling_lessvit.LESSViTModel"
}
}
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