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COMPANY · ENTITY #11108

Hugging Face Hub

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3

MODELS · 1 SOURCE · AWS Machine Learning

Z.ai GLM 5.3 (753B MoE) now available on Amazon Bedrock

Z.ai’s GLM 5.3, a 753‑billion‑parameter mixture‑of‑experts model optimized for coding and long‑horizon agentic tasks and reported to show strong cybersecurity performance, is now available to eligible enterprise customers via Amazon Bedrock. The Bedrock integration offers OpenAI‑compatible APIs (Responses and Chat Completions), Bedrock Invoke/Converse, cross‑Region inference, implicit/explicit prompt caching, and service tiers to simplify managed access and reduce latency and cost.

7.0

MODELS · 1 SOURCE · Hugging Face

Open TTS Leaderboard launches objective, scalable evaluation for multilingual TTS and voice cloning

The Open TTS Leaderboard is an open evaluation platform that ranks TTS models using objective metrics—intelligibility (WER/CER via Qwen3 ASR), speaker similarity (cosine SIM via WavLM), and speed (RTFx and TTFA measured on H200/CPU)—across Seed TTS Eval and CV3 Eval datasets. It supports multilingual and voice-cloning comparisons, provides Pareto visualizations and a Listen tab to audition outputs, and aims to speed evaluation from weeks to hours.

6.0

COMPANIES · 1 SOURCE · Hugging Face

Hugging Face Hub adds dedicated RL Environments dataset filter and framework tags

Hugging Face Hub introduced a dedicated spot for reinforcement-learning environments: dataset repositories tagged rl-environment now appear in a new filter and show generated "Use this dataset" commands plus framework compatibility tags (e.g., Harbor, Verifiers, NVIDIA NeMo Gym, OpenEnv). The release focuses on publishing tasksets (tasks, tests, verifiers) in repo datasets to reduce siloed environment formats and to enable running and verifying tasks via Harbor, NeMo Gym, and Hugging Face Jobs/Sandboxes.

6.0