Instructions to use OPPOer/FaceScore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OPPOer/FaceScore with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OPPOer/FaceScore", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload 2 files
Browse files
FaceScore_model/FS_model.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:50633d6a34bac94fad848389ee19c6a76b76eb9fc5a751c93a5d93e1c9318e25
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size 1786941915
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FaceScore_model/med_config.json
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{
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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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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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": 12,
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"pad_token_id": 0,
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"type_vocab_size": 2,
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"vocab_size": 30524,
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"encoder_width": 768,
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"add_cross_attention": true }
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