This post presents how two open-source frameworks,Alpa.aiandRay.io, work together to achieve the scale required to train a 175 billion-parameterJAX transformermodel with pipeline parallelism. We provide a detailed exploration of these two integrated frameworks, as well as their combined architec...
which are customized for transformer architecture and optimized for the speed in mixed precision (FP16) pretraining. This not only significantly improves the efficiency of transformer training and inference by 20%, but also provides better numerical st...
Short inference times are crucial in scaling DNA hybridisation computations for the zettabyte future. To study this aspect, we perform a comprehensive empirical evaluation of the time required for the forward pass, i.e., prediction time. The choice of experimental platforms is described in detail ...
Practical tricks: FlashAttention-2, Unsloth, Liger Kernel, RoPE scaling, NEFTune and rsLoRA. Experiment monitors: LlamaBoard, TensorBoard, Wandb, MLflow, etc. Faster inference: OpenAI-style API, Gradio UI and CLI with vLLM worker. Benchmark Compared to ChatGLM's P-Tuning, LLaMA Factory's ...
He is currently focused on generative AI, LLMs, prompt engineering, large model inference optimization, and scaling ML across enterprises. Vikram helps financial and insurance industry customers with design and architecture to build and deploy ML applications ...
Practical tricks: FlashAttention-2, Unsloth, Liger Kernel, RoPE scaling, NEFTune and rsLoRA. Experiment monitors: LlamaBoard, TensorBoard, Wandb, MLflow, etc. Faster inference: OpenAI-style API, Gradio UI and CLI with vLLM worker. Benchmark Compared to ChatGLM's P-Tuning, LLaMA Factory's ...
He is currently focused on generative AI, LLMs, prompt engineering, large model inference optimization, and scaling ML across enterprises. Vikram helps financial and insurance industry customers with design and architecture to build and deploy ML a...
Practical tricks: FlashAttention-2, Unsloth, Liger Kernel, RoPE scaling, NEFTune and rsLoRA. Experiment monitors: LlamaBoard, TensorBoard, Wandb, MLflow, etc. Faster inference: OpenAI-style API, Gradio UI and CLI with vLLM worker. Benchmark Compared to ChatGLM's P-Tuning, LLaMA Factory's ...
Practical tricks: FlashAttention-2, Unsloth, Liger Kernel, RoPE scaling, NEFTune and rsLoRA. Experiment monitors: LlamaBoard, TensorBoard, Wandb, MLflow, etc. Faster inference: OpenAI-style API, Gradio UI and CLI with vLLM worker. Benchmark Compared to ChatGLM's P-Tuning, LLaMA Factory's ...
Practical tricks:FlashAttention-2,Unsloth,Liger Kernel, RoPE scaling, NEFTune and rsLoRA. Experiment monitors: LlamaBoard, TensorBoard, Wandb, MLflow, etc. Faster inference: OpenAI-style API, Gradio UI and CLI with vLLM worker. Benchmark ...