KL3M
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About
KL3M is the first clean LLM, focusing on language models without IP or toxicity issues. It's trained on high-quality content with clear provenance, avoiding copyright violations, contract breaches, synthetic data from other LLMs, and toxic sources. KL3M models are efficient, even outperforming larger models on certain tasks. They are already being used for drafting and revising legal documents, SEC filings, and more. KL3M offers several uses, including continued training on your content, fine-tuning for various purposes, and licensing of its training data.
Platform
Task
Features
• high-quality content
• no copyright issues
• no toxic sources
• no llm synthetic data
• no breach of contract
• clean provenance
• fairly trained
FAQs
What kind of hardware do I need to run KL3M?
The first KL3M models have been designed with accessible use as a priority. kl3m-170 runs quickly on a MacBook Air M1, and kl3m-1.7b runs well on a $300 consumer GPU.
What architectures are your models?
Smaller KL3M models are trained using the GPT-NeoX architecture. Larger KL3M models are trained using the Mixtral Mixture-of-Experts architecture (trained from scratch).
How can I run KL3M?
KL3M is distributed as standard PyTorch model weights. KL3M architectures are supported for both HuggingFace transformers and vllm for inference.
Which languages are supported?
`kl3m-170m` and `kl3m-1.7b` have both been trained on a predominantly English-language content. Larger models include content in English, Spanish (es-ES and es-MX), French, and German. We are working on adding more languages.
Do you provide an API?
Not yet. Our focus has been on enabling the use of small, local LLMs for information security and accessibility purposes, but we are evaluating the possibility of providing an API in the future.
Is it easy to fine-tune KL3M?
We have had excellent results fine-tuning KL3M on a number of use cases, including drafting, summarization, and classification. You can fine-tune kl3m-170 and kl3m-1.7b on consumer hardware.
How many tokens do you have?
We have collected over 2.5 trillion tokens of training data, and we are constantly adding more. Our training data is a mix of public domain and explicitly licensed content.
How many tokens have your models seen?
`kl3m-170m` and `kl3m-1.7b` have been trained on approximately 350B tokens of primarily English-language content. Larger models are being trained on between 500B to 1T tokens of content in English, Spanish, French, and German.
Do you have a conversational chat model?
Not yet. While our pretraining data does include a number of conversational sources, we have not yet trained a model that is designed for standard conversational rounds. Stay tuned.
Do you have a general instruction-aligned model?
Our base models already support a number of tasks like extractive/abstractive summarization or conversion, but we have not trained an open-ended model. Our first instruct model supports legal drafting and revision, and we'd love to hear what other tasks you'd like supported.
How do you pronounce KL3M?
As the 🍊 suggests, KL3M is pronounced like "Clem" or "Klem."
Why is it named KL3M?
KL3M was originally short for the Kelvin Legal Large Language Model, KLLLM. Because we're nerds, we shortened all those Ls to L cubed or L3, then shortened K-L3-M to KL3M.
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