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3Hugging Face Blog·1mo ago

Accelerating Protein Language Model ProtST on Intel Gaudi 2

A Hugging Face blog post details the acceleration of ProtST, a protein language model, on Intel's Gaudi 2 AI accelerator hardware. The post covers the technical integration and performance results of running this specialized biological ML model on Gaudi 2. This represents an intersection of domain-specific AI (protein modeling) and alternative AI hardware ecosystems.

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Related events (8)

3Hugging Face Blog·1mo ago·source ↗

Accelerating Vision-Language Models: BridgeTower on Habana Gaudi2

This Hugging Face blog post covers the deployment and acceleration of BridgeTower, a vision-language model, on Intel's Habana Gaudi2 AI accelerator hardware. The piece likely benchmarks inference throughput and training performance on Gaudi2 compared to other hardware. It represents a practical infrastructure and deployment case study for multimodal models on alternative AI accelerators.

4Hugging Face Blog·1mo ago·source ↗

Faster Assisted Generation Support for Intel Gaudi

Hugging Face has published a blog post detailing assisted generation (speculative decoding) support optimized for Intel Gaudi accelerators. The post covers implementation details and performance improvements achieved by running assisted/speculative decoding on Gaudi hardware. This represents an infrastructure and inference optimization development relevant to non-NVIDIA AI accelerator deployment.

4Hugging Face Blog·1mo ago·source ↗

Fast Inference on Large Language Models: BLOOMZ on Habana Gaudi2 Accelerator

This Hugging Face blog post covers deploying BLOOMZ, a large multilingual language model, on Intel's Habana Gaudi2 accelerator for inference. It benchmarks throughput and latency performance on Gaudi2 as an alternative to GPU-based inference. The post is part of ongoing work to demonstrate non-NVIDIA hardware options for large model deployment.

4Hugging Face Blog·1mo ago·source ↗

Accelerating LLM Inference with TGI on Intel Gaudi

Hugging Face's Text Generation Inference (TGI) framework has added a backend for Intel Gaudi accelerators, enabling LLM inference on Intel's AI hardware. The integration allows users to deploy large language models on Gaudi hardware using TGI's serving infrastructure. This expands the hardware ecosystem for LLM inference beyond NVIDIA GPUs, offering an alternative accelerator option for enterprise deployments.

4Hugging Face Blog·1mo ago·source ↗

Text-Generation Pipeline on Intel® Gaudi® 2 AI Accelerator

Hugging Face published a blog post detailing how to run text-generation pipelines on Intel's Gaudi 2 AI accelerator. The post covers integration between Hugging Face's text-generation tooling and Intel's Gaudi 2 hardware, positioning it as an alternative inference accelerator to NVIDIA GPUs. This is relevant to the growing ecosystem of non-NVIDIA AI inference hardware.

4Hugging Face Blog·1mo ago·source ↗

Accelerating Stable Diffusion Inference on Intel CPUs

This Hugging Face blog post details techniques for optimizing Stable Diffusion inference on Intel CPUs, likely covering quantization, operator fusion, and Intel-specific hardware acceleration libraries. The post addresses the practical challenge of running diffusion models on CPU hardware without dedicated GPUs. This is relevant to inference economics and enterprise deployment patterns where GPU availability is constrained.

4Hugging Face Blog·1mo ago·source ↗

Getting Started with Transformers on Habana Gaudi

This Hugging Face blog post introduces integration between the Transformers library and Habana Gaudi AI accelerators. It provides a practical guide for running transformer model training and inference on Gaudi hardware as an alternative to GPU-based infrastructure. The post signals growing ecosystem support for non-NVIDIA AI accelerator hardware.

4Hugging Face Blog·1mo ago·source ↗

Building Cost-Efficient Enterprise RAG Applications with Intel Gaudi 2 and Intel Xeon

This Hugging Face blog post details how to build retrieval-augmented generation (RAG) pipelines for enterprise use cases using Intel Gaudi 2 accelerators and Intel Xeon CPUs. It covers the architecture and cost-efficiency tradeoffs of deploying RAG on Intel hardware as an alternative to GPU-based infrastructure. The post is positioned as a practical guide for organizations seeking lower-cost inference deployments.