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[next-mdx-remote-client] error compiling MDX: Could not parse expression with acorn More information: https://mdxjs.com/docs/troubleshooting-mdx
A 27B-class language model packaged in GGUF with end-to-end ternary weights for on-device or single-GPU llama.cpp inference; reduces FP16 footprint to ~5.9–7.2 GB while retaining ~98% of baseline performance and supporting up to 262K tokens.
[next-mdx-remote-client] error compiling MDX: Could not parse expression with acorn More information: https://mdxjs.com/docs/troubleshooting-mdx
Refines 768P video drafts into 2560×1440 output using MiniMax-H3, latent upscaling, and three diffusion steps. The reported runtime for a 5-second clip is 22.45 seconds on one B200.
Applies a targeted safety-ablation edit to Liquid AI’s LFM3-1.7B and distributes it in quantized GGUF formats. The model card reports fewer refusals on harmful prompts while retaining the base model’s MMLU score.
Generates speech from text and can clone a voice from a reference recording without fine-tuning. The 601M-parameter model supports 23 languages, though output quality varies by language.