Instructions to use APaul1/segformer-scene-parse-150-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use APaul1/segformer-scene-parse-150-lora with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("APaul1/segformer-scene-parse-150-lora") model = SegformerForSemanticSegmentation.from_pretrained("APaul1/segformer-scene-parse-150-lora") - Notebooks
- Google Colab
- Kaggle
Upload 3 files
Browse files- adapter_config.json +32 -0
- adapter_model.safetensors +3 -0
- training_args.bin +3 -0
adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": {
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"base_model_class": "SegformerForSemanticSegmentation",
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"parent_library": "transformers.models.segformer.modeling_segformer"
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},
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"base_model_name_or_path": "nvidia/mit-b0",
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"bias": "lora_only",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"decode_head"
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],
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query",
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"value"
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],
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"task_type": null,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5c6be9adf539220b936650e9d1a810c74aa61ed5d8ba64d9f356c9aa030c11f
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size 2266120
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:555b08bcca49c092dd3625b88f2bb3aa302af3ced28a4af88ca17b0b720bd512
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size 4728
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