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Updated Home (markdown)

Daniel Han 2024-10-31 02:25:49 -07:00
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@ -1008,7 +1008,7 @@ We value engineers who are proactive, independent and who ship features and idea
**!! On our criteria for being considered for an internship / full time role !!**
1. Debug, solve urgent issues / bugs and make 3 merged PRs for interns / 6 merged PRs for a full time engineer
2. **OR** Create a high quality PR on 1 item below (only 1 needed):
2. **OR** Create a high quality accepted PR on 1 item below (only 1 needed):
* Somewhat optimized QLoRA for FLUX / stable diffusion models. Diffusers just added 4bit QLoRA support - make this faster. Provide a Colab notebook tutorial on how to use it. Must fit in 1 x 16GB Tesla T4.
* Unoptimized Apple Silicon / Metal support LoRA - MLX, Core ML Tools etc support.
* Utilities to export Unsloth finetunes to vLLM, SGLang & Ollama - LoRA adapters only. Provide a standalone serving interface to vLLM, SGLang
@ -1019,6 +1019,8 @@ We value engineers who are proactive, independent and who ship features and idea
* Add fully optimized Deepseek finetuning support - investigate [Scatter MoE](https://github.com/shawntan/scattermoe) - confirm loss curves match.
* Add full finetuning / pretraining support in Unsloth - Triton kernels for all.
* FSDPv2 + QLoRA (maybe via Torch AO) + `torch.compile`. Investigate PyTorch native Pipeline, Sequence & Tensor parallelism.
* Using spot instances to train models with a checkpoint recovery mechanism (like SkyPilot)
* Use binary tensor cores for fast Hamming distances for approximate nearest neighbors
**For for details, email me, or ask me questions on Discord! For more information about us, see our:**
1. CUDA / GPU Mode lecture Talk. [Youtube link](https://www.youtube.com/watch?v=hfb_AIhDYnA)