Back to directory

WeClone

A one-stop tool for creating a personal AI chat persona from exported chat history, fine-tuning a language model on the logs to match an individual's writing style and connecting the result to a chatbot.

WeClone

WeClone fine-tunes a language model on a person's own chat history to reproduce their writing style, then connects the tuned model to a chatbot, creating a personal digital avatar. It covers the full pipeline: exporting chat data, preprocessing it, training the model, and deploying the result.

It supports fine-tuning with image data alongside text for more authentic results, includes privacy filtering so sensitive information can be removed before training, and runs training and deployment locally for data control. Chat history can be imported from Telegram, with WhatsApp support planned, and the resulting chatbot can be deployed to Telegram, Discord, Slack or personal WeChat.

By default it fine-tunes the Qwen2.5-VL-7B-Instruct model with LoRA. The project notes it is still in rapid iteration, and that larger base models and more training data tend to produce better results. It is released under the AGPL-3.0 license.

More in Models

See all 405
  • mini-AGI

    github.com

    A continual learning language model that trains from scratch on a single 8 GB VRAM GPU, assembling its own architecture and adapting its size to the hardware and data available rather than shipping as a fixed pretrained model.

  • An open-source contrastive-embedding pipeline that maps technical CVE vulnerability descriptions to formal cybersecurity compliance controls in NIST SP 800-53 and CMMC, published with its model generation, fine-tuning and evaluation code.

  • peekaboolean

    github.com

    A small vision-language model, fine-tuned with LoRA on a 500-million-parameter backbone, that answers typed multiple-choice, ordinal-score and yes/no questions about an image with calibrated probabilities, in about 400 milliseconds on a laptop.