alleniver alleniver

🤗Huggingface Model Downloader

Considering the lack of multi-threaded download support in the official huggingface-cli, and the inadequate error handling in hf_transfer, this command-line tool smartly utilizes wget or aria2 for LFS files and git clone for the rest.

Features

⏯️ Resume from breakpoint: You can re-run it or Ctrl+C anytime.
🚀 Multi-threaded Download: Utilize multiple threads to speed up the download process.
🚫 File Exclusion: Use --exclude or --include to skip or specify files, save time for models with duplicate formats (e.g., *.bin or *.safetensors).
🔐 Auth Support: For gated models that require Huggingface login, use --hf_username and --hf_token to authenticate.
🪞 Mirror Site Support: Set up with HF_ENDPOINT environment variable.

	def forward(self, x, timesteps=None, context=None, y=None, **kwargs):
	# broadcast timesteps to batch dimension
	timesteps = timesteps.expand(x.shape[0])

	hs = []
	t_emb = get_timestep_embedding(timesteps, self.model_channels) # , repeat_only=False)
	t_emb = t_emb.to(x.dtype)
	emb = self.time_embed(t_emb)

	assert x.shape[0] == y.shape[0], f"batch size mismatch: {x.shape[0]} != {y.shape[0]}"

	"""
	stable diffusion dreaming
	creates hypnotic moving videos by smoothly walking randomly through the sample space

	example way to run this script:

	$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

	to stitch together the images, e.g.:
	$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4