xinference docker 部署方式

简绍

Xorbits Inference (Xinference) 是一个开源平台，用于简化各种 AI 模型的运行和集成。借助 Xinference，您可以使用任何开源 LLM、嵌入模型和多模态模型在云端或本地环境中运行推理，并创建强大的 AI 应用。

docker 安装方式

docker 下载对应的 xinference

docker pull xprobe/xinference

docker 运行，注意 路径改成自己的，

docker run  -d  --name xinference --gpus all  -v E:/docker/xinference/models:/root/models  -v E:/docker/xinference/.xinference:/root/.xinference -v E:/docker/xinference/.cache/huggingface:/root/.cache/huggingface -e XINFERENCE_HOME=/root/models  -p 9997:9997 xprobe/xinference:latest xinference-local -H 0.0.0.0

• -d: 让容器在后台运行。
• --name xinference: 为容器指定一个名称，这里是xinference。
• --gpus all: 允许容器访问主机上的所有GPU，这对于需要进行大量计算的任务（如机器学习模型的推理）非常有用。
• -v E:/docker/xinference/models:/root/models, -v E:/docker/xinference/.xinference:/root/.xinference, -v E:/docker/xinference/.cache/huggingface:/root/.cache/huggingface: 这些参数用于将主机的目录挂载到容器内部的特定路径，以便于数据持久化和共享。例如，第一个挂载是将主机的E:/docker/xinference/models目录映射到容器内的/root/models目录。
• -e XINFERENCE_HOME=/root/models: 设置环境变量XINFERENCE_HOME，其值为/root/models，这可能是在容器内配置某些应用行为的方式。
• -p 9997:9997: 将主机的9997端口映射到容器的9997端口，允许外部通过主机的该端口访问容器的服务。
• xprobe/xinference:latest: 指定要使用的镜像和标签，这里使用的是xprobe/xinference镜像的latest版本。
• xinference-local -H 0.0.0.0: 在容器启动时执行的命令，看起来像是以本地模式运行某个服务，并监听所有网络接口。

访问地址

http://127.0.0.1:9997/

对应官网

https://inference.readthedocs.io/zh-cn/latest/index.html

在 dify 中 添加 xinference 容器

docker dify 添加 docker 容器内ip 配置

http://host.docker.internal:9997

内置大语言模型

MODEL NAME	ABILITIES	COTNEXT_LENGTH	DESCRIPTION
aquila2	generate	2048	Aquila2 series models are the base language models
aquila2-chat	chat	2048	Aquila2-chat series models are the chat models
aquila2-chat-16k	chat	16384	AquilaChat2-16k series models are the long-text chat models
baichuan-2	generate	4096	Baichuan2 is an open-source Transformer based LLM that is trained on both Chinese and English data.
baichuan-2-chat	chat	4096	Baichuan2-chat is a fine-tuned version of the Baichuan LLM, specializing in chatting.
c4ai-command-r-v01	chat	131072	C4AI Command-R(+) is a research release of a 35 and 104 billion parameter highly performant generative model.
code-llama	generate	100000	Code-Llama is an open-source LLM trained by fine-tuning LLaMA2 for generating and discussing code.
code-llama-instruct	chat	100000	Code-Llama-Instruct is an instruct-tuned version of the Code-Llama LLM.
code-llama-python	generate	100000	Code-Llama-Python is a fine-tuned version of the Code-Llama LLM, specializing in Python.
codegeex4	chat	131072	the open-source version of the latest CodeGeeX4 model series
codeqwen1.5	generate	65536	CodeQwen1.5 is the Code-Specific version of Qwen1.5. It is a transformer-based decoder-only language model pretrained on a large amount of data of codes.
codeqwen1.5-chat	chat	65536	CodeQwen1.5 is the Code-Specific version of Qwen1.5. It is a transformer-based decoder-only language model pretrained on a large amount of data of codes.
codeshell	generate	8194	CodeShell is a multi-language code LLM developed by the Knowledge Computing Lab of Peking University.
codeshell-chat	chat	8194	CodeShell is a multi-language code LLM developed by the Knowledge Computing Lab of Peking University.
codestral-v0.1	generate	32768	Codestrall-22B-v0.1 is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash
cogagent	chat, vision	4096	The CogAgent-9B-20241220 model is based on GLM-4V-9B, a bilingual open-source VLM base model. Through data collection and optimization, multi-stage training, and strategy improvements, CogAgent-9B-20241220 achieves significant advancements in GUI perception, inference prediction accuracy, action space completeness, and task generalizability.
cogvlm2	chat, vision	8192	CogVLM2 have achieved good results in many lists compared to the previous generation of CogVLM open source models. Its excellent performance can compete with some non-open source models.
cogvlm2-video-llama3-chat	chat, vision	8192	CogVLM2-Video achieves state-of-the-art performance on multiple video question answering tasks.
csg-wukong-chat-v0.1	chat	32768	csg-wukong-1B is a 1 billion-parameter small language model(SLM) pretrained on 1T tokens.
deepseek	generate	4096	DeepSeek LLM, trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese.
deepseek-chat	chat	4096	DeepSeek LLM is an advanced language model comprising 67 billion parameters. It has been trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese.
deepseek-coder	generate	16384	Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese.
deepseek-coder-instruct	chat	16384	deepseek-coder-instruct is a model initialized from deepseek-coder-base and fine-tuned on 2B tokens of instruction data.
deepseek-r1	chat	163840	DeepSeek-R1, which incorporates cold-start data before RL. DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
deepseek-r1-distill-llama	chat	131072	deepseek-r1-distill-llama is distilled from DeepSeek-R1 based on Llama
deepseek-r1-distill-qwen	chat	131072	deepseek-r1-distill-qwen is distilled from DeepSeek-R1 based on Qwen
deepseek-v2	generate	128000	DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference.
deepseek-v2-chat	chat	128000	DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference.
deepseek-v2-chat-0628	chat	128000	DeepSeek-V2-Chat-0628 is an improved version of DeepSeek-V2-Chat.
deepseek-v2.5	chat	128000	DeepSeek-V2.5 is an upgraded version that combines DeepSeek-V2-Chat and DeepSeek-Coder-V2-Instruct. The new model integrates the general and coding abilities of the two previous versions.
deepseek-v3	chat	163840	DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token.
deepseek-vl-chat	chat, vision	4096	DeepSeek-VL possesses general multimodal understanding capabilities, capable of processing logical diagrams, web pages, formula recognition, scientific literature, natural images, and embodied intelligence in complex scenarios.
gemma-2-it	chat	8192	Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.
gemma-it	chat	8192	Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.
glm-4v	chat, vision	8192	GLM4 is the open source version of the latest generation of pre-trained models in the GLM-4 series launched by Zhipu AI.
glm-edge-chat	chat	8192	The GLM-Edge series is our attempt to face the end-side real-life scenarios, which consists of two sizes of large-language dialogue models and multimodal comprehension models (GLM-Edge-1.5B-Chat, GLM-Edge-4B-Chat, GLM-Edge-V-2B, GLM-Edge-V-5B). Among them, the 1.5B / 2B model is mainly for platforms such as mobile phones and cars, and the 4B / 5B model is mainly for platforms such as PCs.
glm-edge-v	chat, vision	8192	The GLM-Edge series is our attempt to face the end-side real-life scenarios, which consists of two sizes of large-language dialogue models and multimodal comprehension models (GLM-Edge-1.5B-Chat, GLM-Edge-4B-Chat, GLM-Edge-V-2B, GLM-Edge-V-5B). Among them, the 1.5B / 2B model is mainly for platforms such as mobile phones and cars, and the 4B / 5B model is mainly for platforms such as PCs.
glm4-chat	chat, tools	131072	GLM4 is the open source version of the latest generation of pre-trained models in the GLM-4 series launched by Zhipu AI.
glm4-chat-1m	chat, tools	1048576	GLM4 is the open source version of the latest generation of pre-trained models in the GLM-4 series launched by Zhipu AI.
gorilla-openfunctions-v2	chat	4096	OpenFunctions is designed to extend Large Language Model (LLM) Chat Completion feature to formulate executable APIs call given natural language instructions and API context.
gpt-2	generate	1024	GPT-2 is a Transformer-based LLM that is trained on WebTest, a 40 GB dataset of Reddit posts with 3+ upvotes.
internlm2-chat	chat	32768	The second generation of the InternLM model, InternLM2.
internlm2.5-chat	chat	32768	InternLM2.5 series of the InternLM model.
internlm2.5-chat-1m	chat	262144	InternLM2.5 series of the InternLM model supports 1M long-context
internlm3-instruct	chat, tools	32768	InternLM3 has open-sourced an 8-billion parameter instruction model, InternLM3-8B-Instruct, designed for general-purpose usage and advanced reasoning.
internvl-chat	chat, vision	32768	InternVL 1.5 is an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding.
internvl2	chat, vision	32768	InternVL 2 is an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding.
llama-2	generate	4096	Llama-2 is the second generation of Llama, open-source and trained on a larger amount of data.
llama-2-chat	chat	4096	Llama-2-Chat is a fine-tuned version of the Llama-2 LLM, specializing in chatting.
llama-3	generate	8192	Llama 3 is an auto-regressive language model that uses an optimized transformer architecture
llama-3-instruct	chat	8192	The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks..
llama-3.1	generate	131072	Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture
llama-3.1-instruct	chat, tools	131072	The Llama 3.1 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks..
llama-3.2-vision	generate, vision	131072	The Llama 3.2-Vision instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image…
llama-3.2-vision-instruct	chat, vision	131072	Llama 3.2-Vision instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image…
llama-3.3-instruct	chat, tools	131072	The Llama 3.3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks..
marco-o1	chat, tools	32768	Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
minicpm-2b-dpo-bf16	chat	4096	MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
minicpm-2b-dpo-fp16	chat	4096	MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
minicpm-2b-dpo-fp32	chat	4096	MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
minicpm-2b-sft-bf16	chat	4096	MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
minicpm-2b-sft-fp32	chat	4096	MiniCPM is an End-Size LLM developed by ModelBest Inc. and TsinghuaNLP, with only 2.4B parameters excluding embeddings.
minicpm-llama3-v-2_5	chat, vision	8192	MiniCPM-Llama3-V 2.5 is the latest model in the MiniCPM-V series. The model is built on SigLip-400M and Llama3-8B-Instruct with a total of 8B parameters.
minicpm-v-2.6	chat, vision	32768	MiniCPM-V 2.6 is the latest model in the MiniCPM-V series. The model is built on SigLip-400M and Qwen2-7B with a total of 8B parameters.
minicpm3-4b	chat	32768	MiniCPM3-4B is the 3rd generation of MiniCPM series. The overall performance of MiniCPM3-4B surpasses Phi-3.5-mini-Instruct and GPT-3.5-Turbo-0125, being comparable with many recent 7B~9B models.
mistral-instruct-v0.1	chat	8192	Mistral-7B-Instruct is a fine-tuned version of the Mistral-7B LLM on public datasets, specializing in chatting.
mistral-instruct-v0.2	chat	8192	The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an improved instruct fine-tuned version of Mistral-7B-Instruct-v0.1.
mistral-instruct-v0.3	chat	32768	The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an improved instruct fine-tuned version of Mistral-7B-Instruct-v0.1.
mistral-large-instruct	chat	131072	Mistral-Large-Instruct-2407 is an advanced dense Large Language Model (LLM) of 123B parameters with state-of-the-art reasoning, knowledge and coding capabilities.
mistral-nemo-instruct	chat	1024000	The Mistral-Nemo-Instruct-2407 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-Nemo-Base-2407
mistral-v0.1	generate	8192	Mistral-7B is a unmoderated Transformer based LLM claiming to outperform Llama2 on all benchmarks.
mixtral-8x22b-instruct-v0.1	chat	65536	The Mixtral-8x22B-Instruct-v0.1 Large Language Model (LLM) is an instruct fine-tuned version of the Mixtral-8x22B-v0.1, specializing in chatting.
mixtral-instruct-v0.1	chat	32768	Mistral-8x7B-Instruct is a fine-tuned version of the Mistral-8x7B LLM, specializing in chatting.
mixtral-v0.1	generate	32768	The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.
omnilmm	chat, vision	2048	OmniLMM is a family of open-source large multimodal models (LMMs) adept at vision & language modeling.
openhermes-2.5	chat	8192	Openhermes 2.5 is a fine-tuned version of Mistral-7B-v0.1 on primarily GPT-4 generated data.
opt	generate	2048	Opt is an open-source, decoder-only, Transformer based LLM that was designed to replicate GPT-3.
orion-chat	chat	4096	Orion-14B series models are open-source multilingual large language models trained from scratch by OrionStarAI.
orion-chat-rag	chat	4096	Orion-14B series models are open-source multilingual large language models trained from scratch by OrionStarAI.
phi-2	generate	2048	Phi-2 is a 2.7B Transformer based LLM used for research on model safety, trained with data similar to Phi-1.5 but augmented with synthetic texts and curated websites.
phi-3-mini-128k-instruct	chat	128000	The Phi-3-Mini-128K-Instruct is a 3.8 billion-parameter, lightweight, state-of-the-art open model trained using the Phi-3 datasets.
phi-3-mini-4k-instruct	chat	4096	The Phi-3-Mini-4k-Instruct is a 3.8 billion-parameter, lightweight, state-of-the-art open model trained using the Phi-3 datasets.
platypus2-70b-instruct	generate	4096	Platypus-70B-instruct is a merge of garage-bAInd/Platypus2-70B and upstage/Llama-2-70b-instruct-v2.
qvq-72b-preview	chat, vision	32768	QVQ-72B-Preview is an experimental research model developed by the Qwen team, focusing on enhancing visual reasoning capabilities.
qwen-chat	chat	32768	Qwen-chat is a fine-tuned version of the Qwen LLM trained with alignment techniques, specializing in chatting.
qwen-vl-chat	chat, vision	4096	Qwen-VL-Chat supports more flexible interaction, such as multiple image inputs, multi-round question answering, and creative capabilities.
qwen1.5-chat	chat, tools	32768	Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data.
qwen1.5-moe-chat	chat, tools	32768	Qwen1.5-MoE is a transformer-based MoE decoder-only language model pretrained on a large amount of data.
qwen2-audio	generate, audio	32768	Qwen2-Audio: A large-scale audio-language model which is capable of accepting various audio signal inputs and performing audio analysis or direct textual responses with regard to speech instructions.
qwen2-audio-instruct	chat, audio	32768	Qwen2-Audio: A large-scale audio-language model which is capable of accepting various audio signal inputs and performing audio analysis or direct textual responses with regard to speech instructions.
qwen2-instruct	chat, tools	32768	Qwen2 is the new series of Qwen large language models
qwen2-moe-instruct	chat, tools	32768	Qwen2 is the new series of Qwen large language models.
qwen2-vl-instruct	chat, vision	32768	Qwen2-VL: To See the World More Clearly.Qwen2-VL is the latest version of the vision language models in the Qwen model familities.
qwen2.5	generate	32768	Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters.
qwen2.5-coder	generate	32768	Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen).
qwen2.5-coder-instruct	chat, tools	32768	Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen).
qwen2.5-instruct	chat, tools	32768	Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters.
qwen2.5-vl-instruct	chat, vision	128000	Qwen2.5-VL: Qwen2.5-VL is the latest version of the vision language models in the Qwen model familities.
qwq-32b-preview	chat	32768	QwQ-32B-Preview is an experimental research model developed by the Qwen Team, focused on advancing AI reasoning capabilities.
seallm_v2	generate	8192	We introduce SeaLLM-7B-v2, the state-of-the-art multilingual LLM for Southeast Asian (SEA) languages
seallm_v2.5	generate	8192	We introduce SeaLLM-7B-v2.5, the state-of-the-art multilingual LLM for Southeast Asian (SEA) languages
skywork	generate	4096	Skywork is a series of large models developed by the Kunlun Group · Skywork team.
skywork-math	generate	4096	Skywork is a series of large models developed by the Kunlun Group · Skywork team.
starling-lm	chat	4096	We introduce Starling-7B, an open large language model (LLM) trained by Reinforcement Learning from AI Feedback (RLAIF). The model harnesses the power of our new GPT-4 labeled ranking dataset
telechat	chat	8192	The TeleChat is a large language model developed and trained by China Telecom Artificial Intelligence Technology Co., LTD. The 7B model base is trained with 1.5 trillion Tokens and 3 trillion Tokens and Chinese high-quality corpus.
tiny-llama	generate	2048	The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens.
wizardcoder-python-v1.0	chat	100000
wizardmath-v1.0	chat	2048	WizardMath is an open-source LLM trained by fine-tuning Llama2 with Evol-Instruct, specializing in math.
xverse	generate	2048	XVERSE is a multilingual large language model, independently developed by Shenzhen Yuanxiang Technology.
xverse-chat	chat	2048	XVERSEB-Chat is the aligned version of model XVERSE.
yi	generate	4096	The Yi series models are large language models trained from scratch by developers at 01.AI.
yi-1.5	generate	4096	Yi-1.5 is an upgraded version of Yi. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples.
yi-1.5-chat	chat	4096	Yi-1.5 is an upgraded version of Yi. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples.
yi-1.5-chat-16k	chat	16384	Yi-1.5 is an upgraded version of Yi. It is continuously pre-trained on Yi with a high-quality corpus of 500B tokens and fine-tuned on 3M diverse fine-tuning samples.
yi-200k	generate	262144	The Yi series models are large language models trained from scratch by developers at 01.AI.
yi-chat	chat	4096	The Yi series models are large language models trained from scratch by developers at 01.AI.
yi-coder	generate	131072	Yi-Coder is a series of open-source code language models that delivers state-of-the-art coding performance with fewer than 10 billion parameters.Excelling in long-context understanding with a maximum context length of 128K tokens.Supporting 52 major programming languages, including popular ones such as Java, Python, JavaScript, and C++.
yi-coder-chat	chat	131072	Yi-Coder is a series of open-source code language models that delivers state-of-the-art coding performance with fewer than 10 billion parameters.Excelling in long-context understanding with a maximum context length of 128K tokens.Supporting 52 major programming languages, including popular ones such as Java, Python, JavaScript, and C++.
yi-vl-chat	chat, vision	4096	Yi Vision Language (Yi-VL) model is the open-source, multimodal version of the Yi Large Language Model (LLM) series, enabling content comprehension, recognition, and multi-round conversations about images.

嵌入模型

• bce-embedding-base_v1
• bge-base-en
• bge-base-en-v1.5
• bge-base-zh
• bge-base-zh-v1.5
• bge-large-en
• bge-large-en-v1.5
• bge-large-zh
• bge-large-zh-noinstruct
• bge-large-zh-v1.5
• bge-m3
• bge-small-en-v1.5
• bge-small-zh
• bge-small-zh-v1.5
• e5-large-v2
• gte-base
• gte-large
• gte-Qwen2
• jina-clip-v2
• jina-embeddings-v2-base-en
• jina-embeddings-v2-base-zh
• jina-embeddings-v2-small-en
• jina-embeddings-v3
• m3e-base
• m3e-large
• m3e-small
• multilingual-e5-large
• text2vec-base-chinese
• text2vec-base-chinese-paraphrase
• text2vec-base-chinese-sentence
• text2vec-base-multilingual
• text2vec-large-chinese

• FLUX.1-dev
• FLUX.1-schnell
• GOT-OCR2_0
• HunyuanDiT-v1.2
• HunyuanDiT-v1.2-Distilled
• kolors
• sd-turbo
• sd3-medium
• sd3.5-large
• sd3.5-large-turbo
• sd3.5-medium
• sdxl-turbo
• stable-diffusion-2-inpainting
• stable-diffusion-inpainting
• stable-diffusion-v1.5
• stable-diffusion-xl-base-1.0
• stable-diffusion-xl-inpainting

图像模型

• FLUX.1-dev
• FLUX.1-schnell
• GOT-OCR2_0
• HunyuanDiT-v1.2
• HunyuanDiT-v1.2-Distilled
• kolors
• sd-turbo
• sd3-medium
• sd3.5-large
• sd3.5-large-turbo
• sd3.5-medium
• sdxl-turbo
• stable-diffusion-2-inpainting
• stable-diffusion-inpainting
• stable-diffusion-v1.5
• stable-diffusion-xl-base-1.0
• stable-diffusion-xl-inpainting

音频模型

以下是 Xinference 中内置的音频模型列表:

• Belle-distilwhisper-large-v2-zh
• Belle-whisper-large-v2-zh
• Belle-whisper-large-v3-zh
• ChatTTS
• CosyVoice-300M
• CosyVoice-300M-Instruct
• CosyVoice-300M-SFT
• CosyVoice2-0.5B
• F5-TTS
• F5-TTS-MLX
• FishSpeech-1.5
• Kokoro-82M
• MeloTTS-Chinese
• MeloTTS-English
• MeloTTS-English-v2
• MeloTTS-English-v3
• MeloTTS-French
• MeloTTS-Japanese
• MeloTTS-Korean
• MeloTTS-Spanish
• SenseVoiceSmall
• whisper-base
• whisper-base-mlx
• whisper-base.en
• whisper-base.en-mlx
• whisper-large-v3
• whisper-large-v3-mlx
• whisper-large-v3-turbo
• whisper-large-v3-turbo-mlx
• whisper-medium
• whisper-medium-mlx
• whisper-medium.en
• whisper-medium.en-mlx
• whisper-small
• whisper-small-mlx
• whisper-small.en
• whisper-small.en-mlx
• whisper-tiny
• whisper-tiny-mlx
• whisper-tiny.en
• whisper-tiny.en-mlx

重排序模型

以下是 Xinference 中内置的重排序模型列表:

• bce-reranker-base_v1
• bge-reranker-base
• bge-reranker-large
• bge-reranker-v2-gemma
• bge-reranker-v2-m3
• bge-reranker-v2-minicpm-layerwise
• jina-reranker-v2
• minicpm-reranker

视频模型

以下是 Xinference 中内置的视频模型列表:

• CogVideoX-2b
• CogVideoX-5b
• HunyuanVideo