import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("codemichaeld/wan1.3b_cf_FP8", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]FP8 Model Conversion
- Source:
https://huggingface.co/TalmajM/causal_forcing_framewise_ComfyUI_repackaged - Original File(s):
causal_forcing-framewise.safetensors - Original Format:
safetensors - FP8 Format:
E5M2 - FP8 File:
causal_forcing-framewise-fp8-e5m2.safetensors
Usage
from safetensors.torch import load_file
import torch
# Load FP8 model
fp8_state = load_file("causal_forcing-framewise-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: 825
- Converted to FP8: 825
- Skipped (non-float): 0
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