Instructions to use codemichaeld/zavychromaxl_FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemichaeld/zavychromaxl_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/zavychromaxl_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
FP8 Model Conversion
- Source:
https://huggingface.co/misri/zavychromaxl_v100 - Original File(s):
zavychromaxl_v100.safetensors - Original Format:
safetensors - FP8 Format:
E5M2 - FP8 File:
zavychromaxl_v100-fp8-e5m2.safetensors
Usage
from safetensors.torch import load_file
import torch
# Load FP8 model
fp8_state = load_file("zavychromaxl_v100-fp8-e5m2.safetensors")
# Convert tensors back to float32 for computation (auto-converted by PyTorch)
model.load_state_dict(fp8_state)
Note: FP8 tensors are automatically converted to float32 when loaded in PyTorch. Requires PyTorch ≥ 2.1 for FP8 support.
Statistics
- Total tensors: 2515
- Converted to FP8: 2515
- Skipped (non-float): 0
- Downloads last month
- 19
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