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Running
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Running
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Zero
| title: CogVideoX-2B | |
| emoji: 🎥 | |
| colorFrom: yellow | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 4.41.0 | |
| suggested_hardware: a10g-large | |
| suggested_storage: large | |
| app_port: 7860 | |
| app_file: app.py | |
| models: | |
| - THUDM/CogVideoX-2b | |
| tags: | |
| - cogvideox | |
| - video-generation | |
| - thudm | |
| short_description: Text-to-Video | |
| disable_embedding: false | |
| # CogVideoX HF Space | |
| ## How to run this space | |
| CogVideoX does not rely on any external API models. | |
| However, during the training of CogVideoX, we used relatively long prompts. To enable users to achieve rendering with | |
| shorter prompts, we integrated an LLM to refine the prompts for better results. | |
| This step is not mandatory, but we recommend using an LLM to enhance the prompts. | |
| ### Using with GLM-4 Model | |
| ```shell | |
| OPENAI_BASE_URL=https://open.bigmodel.cn/api/paas/v4/ OPENAI_API_KEY="ZHIPUAI_API_KEY" python gradio_demo.py | |
| ``` | |
| ### Using with OpenAI GPT-4 Model | |
| ```shell | |
| OPENAI_API_KEY="OPENAI_API_KEY" python gradio_demo.py | |
| ``` | |
| and change `app.py` here: | |
| ``` | |
| model="glm-4-0520" # change to GPT-4o | |
| ``` | |
| ### Not using LLM to refine prompts. | |
| ```shell | |
| python gradio_demo.py | |
| ``` |