本地运行大语言模型（large language models）：ollama

Model	Parameters	Size	Download
Llama 3	8B	4.7GB	`ollama run llama3`
Llama 3	70B	40GB	`ollama run llama3:70b`
Phi-3	3.8B	2.3GB	`ollama run phi3`
Mistral	7B	4.1GB	`ollama run mistral`
Neural Chat	7B	4.1GB	`ollama run neural-chat`
Starling	7B	4.1GB	`ollama run starling-lm`
Code Llama	7B	3.8GB	`ollama run codellama`
Llama 2 Uncensored	7B	3.8GB	`ollama run llama2-uncensored`
LLaVA	7B	4.5GB	`ollama run llava`
Gemma	2B	1.4GB	`ollama run gemma:2b`
Gemma	7B	4.8GB	`ollama run gemma:7b`
Solar	10.7B	6.1GB	`ollama run solar`

用于ollama的模型：

https://ollama.com/library/

2.中文相关的几个模型

2.1 llama2-chinese

https://ollama.com/library/llama2-chinese

Llama 2 based model fine tuned to improve Chinese dialogue ability.

ollama run llama2-chinese

2.2 qwen

https://ollama.com/library/qwen

Qwen 1.5 is a series of large language models by Alibaba Cloud spanning from 0.5B to 110B parameters

343.2K Pulls379 TagsUpdated 2 weeks ago

ollama run qwen

2.3 yi

Yi is a series of large language models trained on a high-quality corpus of 3 trillion tokens that support both the English and Chinese languages.

https://ollama.com/library/yi:34b

https://huggingface.co/01-ai

https://huggingface.co/01-ai/Yi-34B

ollama run yi
ollama run yi:9b
ollama run yi:34b

Yi-34B-Chat model landed in second place (following GPT-4 Turbo), outperforming other LLMs (such as GPT-4, Mixtral, Claude) on the AlpacaEval Leaderboard (based on data available up to January 2024

Yi-34B model ranked first among all existing open-source models (such as Falcon-180B, Llama-70B, Claude) in both English and Chinese on various benchmarks, including Hugging Face Open LLM Leaderboard (pre-trained) and C-Eval (based on data available up to November 2023).

本地运行大语言模型（large language models）：ollama

1.ollama

1.1 下载并安装ollama

1.2 Ollama可以载入的大语言模型

2.中文相关的几个模型

2.1 llama2-chinese

2.2 qwen

2.3 yi

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