#🔒 .venv not working

12 messages · Page 1 of 1 (latest)

weary parrot
#

I think the code is exactly the same as in the fireship's video
so why is it not working ?
these are my installed packages

Package                  Version
------------------------ ----------
certifi                  2024.7.4
charset-normalizer       3.3.2
diffusers                0.30.0
filelock                 3.15.4
fsspec                   2024.6.1
huggingface-hub          0.24.6
idna                     3.7
importlib_metadata       8.3.0
Jinja2                   3.1.4
MarkupSafe               2.1.5
mpmath                   1.3.0
networkx                 3.3
numpy                    2.1.0
nvidia-cublas-cu12       12.1.3.1
nvidia-cuda-cupti-cu12   12.1.105
nvidia-cuda-nvrtc-cu12   12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12        9.1.0.70
nvidia-cufft-cu12        11.0.2.54
nvidia-curand-cu12       10.3.2.106
nvidia-cusolver-cu12     11.4.5.107
nvidia-cusparse-cu12     12.1.0.106
nvidia-nccl-cu12         2.20.5
nvidia-nvjitlink-cu12    12.6.20
nvidia-nvtx-cu12         12.1.105
packaging                24.1
pillow                   10.4.0
pip                      24.0
PyYAML                   6.0.2
regex                    2024.7.24
requests                 2.32.3
safetensors              0.4.4
setuptools               73.0.0
sympy                    1.13.2
torch                    2.4.0
tqdm                     4.66.5
triton                   3.0.0
typing_extensions        4.12.2
urllib3                  2.2.2
zipp                     3.20.0
image.png
proven smeltBOT
#

@weary parrot

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weary parrot
#

what is torch_dtype XD

coral vigil
#

hard to tell without the code. I don't suppose you have your code on github? If so, and if I can easily clone it and reproduce your problem, I'll take a look

weary parrot
# coral vigil hard to tell without the code. I don't suppose you have your code on github? I... 
import torch
from diffusers.pipelines.flux.pipeline_flux import FluxPipeline

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_type=torch.bfloat16)
pipe.enable_model_cpu_offload()

prompt = "A homeless cat holding a cardboard sign that says 'hi'"

# Assuming the correct method to generate an image is `generate()`
image = pipe.generate(
    prompt=prompt,
    height=1024,
    width=1024,
    guidance_scale=3.5,
    num_inference_steps=50,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]

image.save("flux-dev.png")
#

this worked

# 
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power

prompt = "A cat holding a sign that says hello world"
image = pipe(
    prompt,
    height=1024,
    width=1024,
    guidance_scale=3.5,
    num_inference_steps=50,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-dev.png")
#

and this did not

proven smeltBOT
#
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