Huggingface lists thousands of open source models. Each one has a page telling you what base model it’s based on, what other models are merged into it, what data its fine-tuned on, etc.
You can search by number of parameters, you can find quantized versions, you can find datasets to fine-tune your own model on.
I don’t know about GUI, but I’m sure there are some out there. Definitely options for API too
Yeah, more people should know about it. There’s really no reason to pay for an API for these giant 200 billion parameter commercial models sucking up intense resources in data centers.
A quantized 24-32 billion parameter model works just fine, can be self-hosted, and can be fine-tuned on ethically-sourced datasets to suit your specific purposes. Bonus points for running your home lab on solar power.
Not only are the commercial models trained on stolen data, but they’re so generalized that they’re basically worthless for any specialized purpose. A 12 billion parameter model with Retrieval-Augmented Generation is far less likely to hallucinate.
Huggingface lists thousands of open source models. Each one has a page telling you what base model it’s based on, what other models are merged into it, what data its fine-tuned on, etc.
You can search by number of parameters, you can find quantized versions, you can find datasets to fine-tune your own model on.
I don’t know about GUI, but I’m sure there are some out there. Definitely options for API too
Huggingface is an absolutly great ressource
Yeah, more people should know about it. There’s really no reason to pay for an API for these giant 200 billion parameter commercial models sucking up intense resources in data centers.
A quantized 24-32 billion parameter model works just fine, can be self-hosted, and can be fine-tuned on ethically-sourced datasets to suit your specific purposes. Bonus points for running your home lab on solar power.
Not only are the commercial models trained on stolen data, but they’re so generalized that they’re basically worthless for any specialized purpose. A 12 billion parameter model with Retrieval-Augmented Generation is far less likely to hallucinate.