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
Download pretraining/architecture.json from GFM-Bench/LESSViT-Base: direct link, hf CLI and curl.
- Browser
- Download file 1.09 kB
-
https://huggingface.co/GFM-Bench/LESSViT-Base/resolve/main/pretraining/architecture.json
- Command line
-
hf download hf://GFM-Bench/LESSViT-Base/pretraining/architecture.json
-
curl -L -o architecture.json https://huggingface.co/GFM-Bench/LESSViT-Base/resolve/main/pretraining/architecture.json
1.09 kB
| { | |
| "architectures": [ | |
| "SpatialSpectralMAEViT" | |
| ], | |
| "attention_radius": 640, | |
| "attn_drop": 0.1, | |
| "channel_dim": 24, | |
| "channel_dropout": [ | |
| 0.75, | |
| 0.85 | |
| ], | |
| "channel_mask_ratio": 0.75, | |
| "decoder_attention_radius": [ | |
| 640 | |
| ], | |
| "decoder_channel_dim": 32, | |
| "decoder_depth": 8, | |
| "decoder_embed_dim": 512, | |
| "decoder_history_length": [ | |
| 4 | |
| ], | |
| "decoder_num_heads": 16, | |
| "decoder_out_chans": 155, | |
| "decoder_out_dims": 1, | |
| "decoder_spatial_dim": 256, | |
| "decoder_temporal_embed_dims_per_head": 4, | |
| "depth": 12, | |
| "drop_path_rate": 0.1, | |
| "drop_path_uniform": false, | |
| "embed_dim": 768, | |
| "init_values": 1.0, | |
| "mask_ratio": 0.75, | |
| "mlp_ratio": 4.0, | |
| "model_type": "multi_modal_low_rank_vit", | |
| "norm_pix_loss": false, | |
| "num_heads": 12, | |
| "patch_size": 16, | |
| "pos_chan_embed_residual": true, | |
| "pretrain": true, | |
| "proj_drop": 0.1, | |
| "qk_norm": false, | |
| "qkv_bias": true, | |
| "rank": 1, | |
| "return_dict": false, | |
| "rope_embed_base": 100.0, | |
| "spatial_dim": 384, | |
| "use_perception_field_mask": true, | |
| "use_rope_embed": true, | |
| "channel_embed_dims_per_head": 2 | |
| } | |