this post was submitted on 13 Nov 2023
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LocalLLaMA

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Community to discuss about Llama, the family of large language models created by Meta AI.

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We are Higgsfield AI. We have a large GPU cluster and want to finetune your dataset. (alien.top)
submitted 1 year ago by RiskApprehensive9770@alien.top to c/localllama@poweruser.forum
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Hey LocalLLaMA. It's Higgsfield AI, and we train huge foundational models.

We have a massive GPU cluster and developed our own infrastructure to manage the cluster and train massive models. We constantly lurked in this subreddit and learned a lot from this passionate community. Right now, we have spare GPUs, and we are excited to give back to this incredible community.

We built a simple web app where you can upload your datasets to finetune it. https://higgsfield.ai/

There's how it works:

  1. You upload the dataset with preconfigured format into HuggingFaсe [1].
  2. Choose your LLM (e.g. LLaMa 70B, Mistral 7B)
  3. Place your submission into the queue
  4. Wait for it to get trained.
  5. Then you get your trained model there on HuggingFace.

[1]: https://github.com/higgsfield-ai/higgsfield/tree/main/tutorials

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[–] RiskApprehensive9770@alien.top 1 points 1 year ago (1 children)

You can train on any dataset as long as it follows our format.

Soon we'll publish a video tutorial.

[–] herozorro@alien.top 1 points 1 year ago

but what would be the proper formatting example for code? just paste in a bunch of files from a repo? or should be more a cheatsheet format?