Instructions to use mountassir/ddpm-flowers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mountassir/ddpm-flowers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mountassir/ddpm-flowers", 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
Epoch 40
Browse files- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/random_states_0.pkl +3 -0
- checkpoint-1000/scaler.pt +3 -0
- checkpoint-1000/scheduler.bin +3 -0
- checkpoint-1000/unet/config.json +51 -0
- checkpoint-1000/unet/diffusion_pytorch_model.safetensors +3 -0
- logs/train_unconditional/events.out.tfevents.1730648693.f38345c6fc4b.17696.0 +2 -2
- unet/diffusion_pytorch_model.safetensors +1 -1
checkpoint-1000/optimizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7a51562f46241312f2334cdce9d67cef880d20265ef72eadeee45559dbe405d3
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size 909763736
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checkpoint-1000/random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:46ca44f949f40fb26f6e367af999f7a46b25f12a8fd9efd107a75f602a531157
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size 14344
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checkpoint-1000/scaler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:9d8fdcd0311eba9854fff738038ed4c1a269832665b4d88ba4e4e3d02a1a7e0e
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size 988
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checkpoint-1000/scheduler.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7249b8abac1a07e3debb443662e9f5004b1cf44ab1f28ca7c3e1851bc395ce6b
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size 1000
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checkpoint-1000/unet/config.json
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{
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"_class_name": "UNet2DModel",
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"_diffusers_version": "0.32.0.dev0",
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"act_fn": "silu",
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"add_attention": true,
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"attention_head_dim": 8,
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"attn_norm_num_groups": null,
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"block_out_channels": [
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128,
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128,
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256,
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256,
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512,
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512
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],
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"center_input_sample": false,
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"class_embed_type": null,
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"down_block_types": [
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"DownBlock2D",
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"DownBlock2D",
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"DownBlock2D",
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"DownBlock2D",
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"AttnDownBlock2D",
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"DownBlock2D"
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],
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"downsample_padding": 1,
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"downsample_type": "conv",
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"dropout": 0.0,
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"flip_sin_to_cos": true,
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"freq_shift": 0,
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"in_channels": 3,
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"layers_per_block": 2,
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"mid_block_scale_factor": 1,
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"norm_eps": 1e-05,
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"norm_num_groups": 32,
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"num_class_embeds": null,
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"num_train_timesteps": null,
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"out_channels": 3,
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"resnet_time_scale_shift": "default",
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"sample_size": 64,
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"time_embedding_type": "positional",
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"up_block_types": [
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"UpBlock2D",
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"AttnUpBlock2D",
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"UpBlock2D",
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"UpBlock2D",
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"UpBlock2D",
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"UpBlock2D"
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],
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"upsample_type": "conv"
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}
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checkpoint-1000/unet/diffusion_pytorch_model.safetensors
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oid sha256:a7ea617911bc4245f336bc56bd8e38251b072836f37c9f567c63db8bf6900047
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size 454741108
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logs/train_unconditional/events.out.tfevents.1730648693.f38345c6fc4b.17696.0
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size 3282465
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unet/diffusion_pytorch_model.safetensors
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size 454741108
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size 454741108
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