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AI 모델 84760
- mms-tts-azj-script_latin↗
facebook
This repository contains the **Azerbaijani, North (azj-script_latin)** language text-to-speech (TTS) model checkpoint. This model is part of Facebook's Massively Multilingual Speech project, aiming to provide speech technology across a diverse range of languages. You can find more details about the supported languages and their ISO 639-3 codes in the MMS Language Coverage Overview, and see all MMS-TTS checkpoints on the Hugging Face Hub: facebook/mms-tts. VITS (**V**ariational **I**nference with adversarial learning for end-to-end **T**ext-to-**S**peech) is an end-to-end speech synthesis model that predicts a speech waveform conditional on an input text sequence. It is a conditional variational autoencoder (VAE) comprised of a posterior encoder, decoder, and conditional prior.
- mms-tts-mwv↗
facebook
- mms-tts-pao↗
facebook
- mms-tts-tnk↗
facebook
- textless_sm_it_fr↗
facebook
- F5-Myanmar-TTS↗
freococo
- EXAONE-4.0-32B-FP8↗
furiosa-ai
This repository contains `LGAI-EXAONE/EXAONE-4.0-32B-FP8` together with a Furiosa Executable Bundle (FXB) for running it on FuriosaAI RNGD with Furiosa-LLM. The same model also runs on other frameworks (such as vLLM, SGLang, and Transformers); for usage with those, see the upstream `LGAI-EXAONE/EXAONE-4.0-32B-FP8` model card. Weights are quantized to **FP8** (static), following the upstream FP8 release, and activations use **dynamic FP8 quantization** at runtime (per-token / per-block). The KV cache stays in 16-bit precision. On RNGD, EXAONE-4.0-32B-FP8 runs with a **tensor-parallel size of 32 PEs**, which maps to **four RNGD cards** (8 PEs per card).
- gemma-4-12B-GGUF↗
ggml-org
- flux2-dev-gguf↗
gguf-org
q2 works (see the one on right) but if you replace it by a higher tier encoder, then it will follow the prompt preciously; wishing you all a very happy Thanksgiving! 🦃
- Gemini 3.1 Flash Lite Preview↗
Google
其性能优于 2.5 Flash，首次响应令牌时间提升 2.5 倍，输出速度提升 45%，同时保持了相似甚至更高的质量