nomic-ai / gpt4all

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
https://nomic.ai/gpt4all
MIT License
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Models: Add Qwen2-1.5B-Instruct #2759

Closed ThiloteE closed 1 month ago

ThiloteE commented 1 month ago

Adds a models3.json entry for Qwen2-1.5B-Instruct

Description of Model

It is a tiny bilingual model and at the date of writing with very strong results in benchmarks (for its parameter size). It supports a context of up to 32768. Because of its model size it has very fast responses, even when doing inference on CPU. This LLM is LITERALLY for all. Since the model fits into 4GB of RAM (just barely, if the Operating System and other apps also need RAM) or alternatively into 3GB of VRAM, this will be the workhorse of the desperate and hardware poor.

Personal Impression:

I got the impression the model is very task focused and this is the reason, why I chose Below is an instruction that describes a task. Write a response that appropriately completes the request. as system prompt. Since the model is relatively small, its responses may seem not very coherent or intelligent, but it works surprisingly well with GPT4All's LocalDocs feature. It is like the model was made for RAG. Its long context adds to that. It mainly will appeal to English and Chinese speaking users.

Checklist before requesting a review

ThiloteE commented 1 month ago

I have added this model at the location "order": "z",, because I fear there might be merge conflicts with #2750

ThiloteE commented 1 month ago

VAGOsolutions confirm its RAG capabilities in their German RAG benchmark: image

cosmic-snow commented 1 month ago

I've downloaded it and checked some fields, and they're all fine: md5sum, name, filename, filesize, quant, type, parameters

I have not looked at their site/blog to verify the templates, however a quick test with them went well.