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*New version available, trained on more data and otherwise identical KennethTM/MiniLM-L6-danish-encoder-v2* This is a lightweight (~22 M parameters) sentence-transformers model for Danish NLP: It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for tasks like clustering or semantic search. The model was not pre-trained from scratch but adapted from the English version of sentence-transformers/all-MiniLM-L6-v2 with a Danish tokenizer.
**svara-TTS** is a developer-first multilingual TTS model for **19 languages** (18 Indic + Indian English). Built on an Orpheus-style discrete audio token approach, it targets **clarity, expressiveness, and low-latency** on commodity GPUs/CPUs. It supports light-weight **emotion/style control** (e.g., ` `, ` `, ` `, ` `) and simple **speaker identities** (`Language (Gender)`), with **zero-shot** adaptation paths. - **Languages (19):** Hindi, Bengali, Marathi, Telugu, Kannada, Bhojpuri, Magahi, Chhattisgarhi, Maithili, Assamese, Bodo, Dogri, Gujarati, Malayalam, Punjabi, Tamil, Nepali, Sanskrit, Indian English. - **Expressivity:** End-of-utterance style tags; natural prosody; code-switch aware. - **Latency & Deployment:** Works well with **GGUF** exports; suitable for edge/CPU scenarios. - **Adaptability:** **LoRA-friendly** for quick speaker/domain specialization. Try it live on the **Demo Space**, or on **Colab** Deployment scripts and **inference repo** will be available soon. Watch our Github for updates
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