Instructions to use meoconxinhxan/ii_training_platform_fishspeech_run_version_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use meoconxinhxan/ii_training_platform_fishspeech_run_version_1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("meoconxinhxan/ii_training_platform_fishspeech_run_version_1", 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
End of training
Browse files
README.md
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@@ -35,10 +35,10 @@ This model was trained using the Fish Speech framework.
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## Model Details
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- Checkpoint: `step_000001000.ckpt`
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- Training Metrics:
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- train/loss: 4.
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- train/base_loss:
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- train/semantic_loss: 3.
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- train/top_5_accuracy: 0.
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- train/grad_norm: 72.0
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- lr-AdamW/pg1: 9.999999747378752e-05
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- lr-AdamW/pg2: 9.999999747378752e-05
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## Model Details
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- Checkpoint: `step_000001000.ckpt`
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- Training Metrics:
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- train/loss: 4.625
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- train/base_loss: 1.0
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- train/semantic_loss: 3.609375
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- train/top_5_accuracy: 0.412109375
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- train/grad_norm: 72.0
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- lr-AdamW/pg1: 9.999999747378752e-05
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- lr-AdamW/pg2: 9.999999747378752e-05
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