evaluation inference interface notebooks server transformers_api example_videollama3.py launch_gradio_demo.py scripts videollama3 .gitignore ACKNOWLEDGEMENT.md LICENSE README.md pyproject.toml requirements.txt vl3_technical_report.pdfBreadcrumbs VideoLLaMA3 / inference/ Directory actions More optionsLatest...
transformers_api example_videollama3.py launch_gradio_demo.py scripts videollama3 .gitignore ACKNOWLEDGEMENT.md LICENSE README.md pyproject.toml requirements.txt vl3_technical_report.pdfBreadcrumbs VideoLLaMA3 /inference/ example_videollama3.pyLatest commit lkhl Update default max_frames a25fe42· Fe...
Anthropic 预计到 2027 年收入将达到 345 亿美元,主要依赖 API 业务。与此同时,OpenAI 也在推进其 Orion 大语言模型,计划与推理模型合并为单一 AI 系统。来源:新智元2.达摩院开源 VideoLLaMA3:7B 模型视频理解能力领先达摩院推出 VideoLLaMA3,一款仅 7B 大小的多模态视频-语言模型,在通用视频理解、时间推理和长...
* v0.15.0 xinference内置客户端chat接口即将废弃prompt, system_prompt 和 chat_history参数,这三个参数将被messages参数替代,与openai形式保持一致 📝 * v0.15.0 Qwen系列的react形式的tool call功能将移除,由OpenAI API形式的tool call代替。移除qwen-chat 1代的tool call能力(不影响qwen1.5-chat和qwen2) ...
inference interface notebooks visuals 01_single_image_understanding.ipynb 02_multi_image_understanding.ipynb 03_visual_referring_and_grounding.ipynb 04_video_understanding.ipynb server transformers_api example_videollama3.py launch_gradio_demo.py scripts videollama3 .gitignore ACKNOWLEDGEMENT.md LICENSE...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...