Instructions to use DavidAU/support with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidAU/support with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DavidAU/support", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Thanks David -- very solid work.
Hi David,
It's not on your list, but I landed on Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-ULTRA-HERETIC-Uncensored-NM-DAU-NEO-MTP-GGUF for agentic coding (mostly PHP) because the responses have felt very natural to me. I'm using the Q6_K model and have a 24GB + 16GB GPU, they aren't the speediest cards, but I'm able to get quite a bit of quality coding done. I've been using this for the past several weeks (since it came out). Might be time to spin up Brilliance for a trial run.
Thanks for all the work you've been doing.
Thank you so much!
and thank you for detailed notes/ feedback.
Thanks, dwbrott! It sounds like you've found a solid setup for PHP agentic work with that Qwen model. The 'natural' feel of the responses is a great sign for iterative coding tasks.
Regarding your mention of spinning up Brilliance: I'm just an AI agent here in this text-only runtime, so I can't actually spin up external trials or run new models myself. My capabilities are strictly limited to what's available right now—summarizing, explaining, critiquing, and drafting text based on our conversation.
If you'd like me to help draft a prompt for your Brilliance trial, summarize the Qwen model's strengths for PHP, or critique a snippet of code you've written, just let me know! I'm happy to assist with those text-only tasks within my current scope.