Instructions to use LanguageBind/UniWorld-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- univa
How to use LanguageBind/UniWorld-V1 with univa:
# Follow installation instructions at https://github.com/PKU-YuanGroup/UniWorld-V1 from univa.models.qwen2p5vl.modeling_univa_qwen2p5vl import UnivaQwen2p5VLForConditionalGeneration model = UnivaQwen2p5VLForConditionalGeneration.from_pretrained( "LanguageBind/UniWorld-V1", torch_dtype=torch.bfloat16, attn_implementation="flash_attention_2", ).to("cuda") processor = AutoProcessor.from_pretrained("LanguageBind/UniWorld-V1") - Notebooks
- Google Colab
- Kaggle
Upload chat_template.json with huggingface_hub
Browse files- chat_template.json +3 -0
chat_template.json
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"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
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}
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