Instructions to use codemichaeld/T5Base_fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemichaeld/T5Base_fp8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codemichaeld/T5Base_fp8", 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
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README.md
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- **Source**: `https://huggingface.co/LifuWang/DistillT5`
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- **File**: `model.safetensors`
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- **FP8 Format**: `E5M2`
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- **Architecture**:
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- **Precision Recovery Type**: LoRA
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- **Precision Recovery File**: `model-lora-r64-
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- **FP8 File**: `model-fp8-e5m2.safetensors`
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## Usage (Inference)
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# Load precision recovery file if available
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recovery_state = {}
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if "model-lora-r64-
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recovery_state = load_file("model-lora-r64-
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# Reconstruct high-precision weights
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reconstructed = {}
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- **Source**: `https://huggingface.co/LifuWang/DistillT5`
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- **File**: `model.safetensors`
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- **FP8 Format**: `E5M2`
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- **Architecture**: all
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- **Precision Recovery Type**: LoRA
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- **Precision Recovery File**: `model-lora-r64-all.safetensors` if available
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- **FP8 File**: `model-fp8-e5m2.safetensors`
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## Usage (Inference)
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# Load precision recovery file if available
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recovery_state = {}
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if "model-lora-r64-all.safetensors":
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recovery_state = load_file("model-lora-r64-all.safetensors")
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# Reconstruct high-precision weights
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reconstructed = {}
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