Instructions to use schrum2/MarioDiffusion-MiniLM-single-regular0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MiniLM-single-regular0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("schrum2/MarioDiffusion-MiniLM-single-regular0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Delete text_encoder/config.json
Browse files- text_encoder/config.json +0 -26
text_encoder/config.json
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{
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"_name_or_path": "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
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"architectures": [
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"BertModel"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 384,
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"initializer_range": 0.02,
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"intermediate_size": 1536,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.48.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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