Img2vid-xt-1-1 File Wasn't on Site

[PhoenixOneA]

Hey all, I was trying to download stabilityai/stable-video-diffusion-img2vid-xt-1-1 but I keep getting the error message “File Wasn’t on Site.” I disabled my antivirus, cleared cookies, and tried incognito with no positive result.

Is this file no longer available? Otherwise, anyone have suggestions on why I wouldn’t be able to download it. Thanks

[John6666]

stabilityai/stable-video-diffusion-img2vid-xt-1-1 · Hugging Face

No, it appears to exist…
Is there some weird behavior going on because it’s a gated model? Does it happen with other models?

[PhoenixOneA]

Yeah, I just saw someone else posted about this a couple of weeks ago in this model’s community tab. I’m pretty new to all of this, so I’m kind of at a loss on what to do next. I’ve not had any issues downloading other models. Any advice?

[John6666]

I’ve read the model repo community you referred to, and it seems like there’s a real possibility that they’re missing some files. In that case, there is nothing we can do.
If it’s just a gated model problem, it can be solved as follows.

How to use gated models?

just wait. I assume they’re US based - so depending on their loc their work week just starts or is going to start. And probably over the weekend there is a number of requests gathering up to be checked. And there’s always possibility that the responsible person isn’t around on day

How to use gated model in inference

You could do it by making the code look like this. Sample code import transformers import torch model_id = "meta-llama/Meta-Llama-3.1-8B-Instruct" pipeline = transformers.pipeline( "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto", ) messages = [ {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, {"role": "user", "content": "Who are you?"}, ] outputs = pipeline( messag…

Access issues for gated repos

hi @sanchitamore This should work. In fact, if you log in, you don’t even need token parameter. from transformers import pipeline class LLM: def __init__(self, model_name, auth_token=None): self.model = pipeline('text2text-generation', model=model_name) def predict(self, prompt, **kwargs): return self.model(text_inputs=prompt, **kwargs)[0]["generated_text"] model = LLM(model_name="mistralai/Mistral-7B-Instruct-v0.3") Can you please run huggingface-cli whoami and do…