This is a preview look at our flagship model, Replete-LLM. This version of the model has only been trained for 1 epoch on the dataset (Linked bellow). The final model will be trained on a full 5 epochs using Qlora and Unsloth.
Replete-LLM is Replete-AI's flagship model. We take pride in releasing a fully open-source, low parameter, and competitive AI model that not only surpasses its predecessor Qwen2-7B-Instruct in performance, but also competes with (if not surpasses) other flagship models such as gemma-2-9b-it
and Meta-Llama-3.1-8B-Instruct in terms of overall performance across all fields and categories.
Replete-LLM-Qwen2-7b is a versatile model fine-tuned to excel on any imaginable task. The following types of generations were included in the fine-tuning process:
Science: (General, Physical Reasoning)
Social Media: (Reddit, Twitter)
General Knowledge: (Character-Codex), (Famous Quotes), (Steam Video Games), (How-To? Explanations)
Cooking: (Cooking Preferences, Recipes)
Writing: (Poetry, Essays, General Writing)
Medicine: (General Medical Data)
History: (General Historical Data)
Law: (Legal Q&A)
Role-Play: (Couple-RP, Roleplay Conversations)
News: (News Generation)
Coding: (3 million rows of coding data in over 100 coding languages)
Math: (Math data from TIGER-Lab/MathInstruct)
Function Calling: (Function calling data from "glaiveai/glaive-function-calling-v2")
General Instruction: (All of teknium/OpenHermes-2.5 fully filtered and uncensored)
At Replete-AI, we hope you utilize our open-source model locally for your work and enjoyment rather than paying companies like OpenAI and Anthropic AI, or anyone who charges fees for using AI models. We believe in complete freedom and openness for AI usage by everyone. Therefore, please enjoy our model and anticipate the final release within a few weeks.
You can find our highest quality quantization that runs under 10gb of vram with 8k context bellow
Note this model in particular was finetuned using an h100 using Tensordock.com using the Pytorch OS. In order to use Unsloth code with TensorDock you need to run the following code (Bellow) to reinstall drivers on TensorDock before unsloth works. After running the code bellow, your Virtual Machine will reset, and you will have to SSH back into it. And then you can run the normal unsloth code in order.
