We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
我用了 Hugging Face 中提供的代码实例
# single-round single-image conversation question = "请详细描述图片" # Please describe the picture in detail response = model.chat(tokenizer, pixel_values, question, generation_config) print(question, response)
并且尝试把其中的 `pixel_values 赋值为 None。类似 llava 一样进行无图推理,但是不能运行。请问有别的方法让 InternVL1.5 进行无图推理吗?
I try to use InternVL1.5 to do inference without Image, like llava model. I copy the demo code from the HuggingFace Repository:
# single-round single-image conversation question = "请详细描述图片" # Please describe the picture in detail response = model.chat(tokenizer, pixel_values, question, generation_config) print(question, response)` 并且尝试把其中的 `pixel_values
And try to give None to pixel_values, but the model is not support it. Is there any other method to make InternVL1.5 do inference without Image?
The text was updated successfully, but these errors were encountered:
No branches or pull requests
我用了 Hugging Face 中提供的代码实例
并且尝试把其中的 `pixel_values 赋值为 None。类似 llava 一样进行无图推理,但是不能运行。请问有别的方法让 InternVL1.5 进行无图推理吗?
I try to use InternVL1.5 to do inference without Image, like llava model. I copy the demo code from the HuggingFace Repository:
And try to give None to pixel_values, but the model is not support it. Is there any other method to make InternVL1.5 do inference without Image?
The text was updated successfully, but these errors were encountered: