#1515th of 19 in Training and fine-tuning
weclone
Fine-tunes a Qwen VL model on your Telegram chats to build a chat avatar
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- Stars
- 18.3k
- License
- AGPL-3.0
- Last commit
- Oct 2026
- Last release
- Jan 2026
- Language
- Python
Missed the latest GitHub check; these facts may be older.
Overview
WeClone exports Telegram chat history, strips personal data with Microsoft Presidio and a blocklist, then LoRA fine-tunes Qwen2.5-VL-7B-Instruct through LLaMA Factory. The tuned model is served as an OpenAI-style API (README example port 8005) and can be connected through AstrBot or LangBot to Telegram, Discord or Slack. Personal WeChat deployment is listed, based on openclaw-weixin.
Who it is for: Hobbyists with an NVIDIA GPU who want a bot that mimics their texting style
Strengths
- Covers the full pipeline: export, PII filtering, LoRA training, API serving, bot deployment
- Presidio redaction plus a manual blocked_words list; encrypted storage default in new templates
- Handles image data; other models usable through LLaMA Factory
- QLoRA 4-bit on a 7B model needs about 6GB VRAM per the README table
Weaknesses
- Only Telegram works as a data source; WhatsApp, Discord and Slack imports are marked planned
- README says 7B results are average; 14B or larger works better
- Fine-tuned model has no tool calling; AstrBot tools must be turned off
- Requires CUDA 12.6+; Windows not rigorously tested (WSL suggested)
What it needs
- GPU required
- Needs CUDA 12.6+, LLaMA Factory, Microsoft Presidio, uv, AstrBot or LangBot (for chat bots)
- Models: Qwen2.5-VL-7B-Instruct, LLaMA Factory supported models, LoRA, QLoRA
- port 8005
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| 1 | unslothDesktop and web app to run, fine-tune and export open models | 88 out of 100 |
| 2 | deepspeedPyTorch library for distributed training of large models with ZeRO | 82 out of 100 |
| 3 | verlReinforcement learning training library for LLM post-training with PPO and GRPO | 77 out of 100 |
| #4 | llamafactoryFine-tuning toolkit for 100+ LLMs with a CLI and Gradio web UI | 75 out of 100 |
| #5 | peftPython library for LoRA and other parameter-efficient fine-tuning of Transformers models | 74 out of 100 |