サイト内検索

AI モデル 84760

• mms-tts-hvn↗

  facebook

• mms-tts-tir↗

  facebook

  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. A set of spectrogram-based acoustic features are predicted by the flow-based module, which is formed of a Transformer-based text encoder and multiple coupling layers. The spectrogram is decoded using a stack of transposed convolutional layers, much in the same style as the HiFi-GAN vocoder. Motivated by the one-to-many nature of the TTS problem, where the same text input can be spoken in multiple ways, the model also includes a stochastic duration predictor, which allows the model to synthesise speech with different rhythms from the same input text.

• gguf-Phi-3-mini-4k-instruct↗

  Felladrin

• KAT-Coder-V2.5-Dev-16GB-MixedQuant-GGUF↗

  fooooooooooooooooooooooooooooooooooooooooo

• segformer-websegcl25-2000-mc-v1↗

  gerbejon

• bge-m3-Q8_0-GGUF↗

  ggml-org

  This model was converted to GGUF format from `BAAI/bge-m3` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

• t5-efficient-large-nl4↗

  Google

• t5-efficient-small-ff1000↗

  Google

• Qwen3.8-Flash-Next-Uncensored-Q4_K_M-MTP↗

  him0413

  An **integrated MTP (Multi-Token Prediction) GGUF** build of the abliterated `Qwen3.8-Flash-Next-Uncensored` model, quantized to **Q4_K_M** with the MTP draft head **merged into the same 4-shard split** — no sidecar file needed. This model is an **abliterated (refusal-removed)** build. It will comply with harmful, unethical, or illegal requests the original `Qwen3.8-Flash-Next` would refuse. Released **strictly for legitimate research** — interpretability, AI-safety / refusal-mechanism study, red-teaming, and robustness evaluation. **You assume full responsibility** for how you use it and everything it generates; add your own safety and moderation layers before any deployment. **Qwen Community License 1.0** (see LICENSE), inherited from the base model `Qwen/Qwen3.8-Flash-Next`. Abliteration and quantization do not change the underlying license obligations.

• HunyuanOCR↗

  腾讯

  🤗 HF Model | 💻 GitHub Repo | 📄 Paper > 📦 **Model layout.** This repository hosts **HunyuanOCR-1.5** checkpoint at the root (target base weights). The **DFlash speculative-decoding draft** lives under `dflash/`, and the previous **HunyuanOCR-1.0** is archived under `v1.0/` (load it with `subfolder="v1.0"`, or download the `v1.0/` directory directly). **HunyuanOCR-1.5** is a lightweight, end-to-end OCR-specialized vision-language model. It targets a broad range of text-centric visual tasks and unifies **document parsing, text spotting, information extraction, text-image translation** within a single end-to-end VLM.