mahimairaja/whisper-small-french-finetuned
Updated
Mahimai Raja J
mahimairaja
AI & ML interests
Azure AI Engineer | LangChain + LangGraph | FastAPI | RAG | Voice AI
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a model 15 days ago
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a model 15 days ago
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a model 15 days ago
mahimairaja/whisper-small-fr Organizations
updated a model 15 days ago
published a model 15 days ago
updated a model 15 days ago
published a model 15 days ago
When will there be better support for vLLM?
6
#6 opened about 1 month ago
by
Xiakj
reacted to marksverdhei's post with 🤗 about 2 months ago
Post
2667
Dear Hugging Face team, can we please have a way to archive hf repositories / spaces? I have a bunch of spaces that used to work but don't any more due to the hf space implementations changing and i think it would be good if I could archive those like in GitHub.
React to this post if you want to see this feature! 💡
React to this post if you want to see this feature! 💡
reacted to Javedalam's post with 🔥 about 2 months ago
Post
2987
KittenTTS Nano — Tiny, Expressive, Practical
KittenTTS Nano is a lightweight, CPU-only text-to-speech model designed to prove that natural, expressive voices don’t require massive cloud stacks or GPUs. At roughly ~15M parameters, it runs fast on modest hardware, supports multiple expressive voices, and exposes simple controls for pacing and tone. This makes it ideal for edge devices, demos, and anyone who wants full control over TTS without latency, lock-in, or infrastructure overhead.
Try it here
Javedalam/KittenTTS
The model page
KittenML/kitten-tts-nano-0.2
KittenTTS Nano is a lightweight, CPU-only text-to-speech model designed to prove that natural, expressive voices don’t require massive cloud stacks or GPUs. At roughly ~15M parameters, it runs fast on modest hardware, supports multiple expressive voices, and exposes simple controls for pacing and tone. This makes it ideal for edge devices, demos, and anyone who wants full control over TTS without latency, lock-in, or infrastructure overhead.
Try it here
Javedalam/KittenTTS
The model page
KittenML/kitten-tts-nano-0.2
- 2 replies
posted an
update about 2 months ago
Post
1186
🔥 Qwen is dominating the SLM space right now.
We all know this year 2026 is the year of Small Models, but Alibaba team took it bit serious it seems!
Qwen3-TTS — 3-sec voice cloning, 10 languages, beats ElevenLabs
Qwen3-ASR — Just dropped TODAY! 52 languages, <8% WER, SOTA open-source ASR
Qwen-Image — #1 open-source image model on AI Arena
All Apache 2.0. The most complete open-source AI stack, period.
So, what do you think now, what next release could be? an Language Model?
Comment below
We all know this year 2026 is the year of Small Models, but Alibaba team took it bit serious it seems!
Qwen3-TTS — 3-sec voice cloning, 10 languages, beats ElevenLabs
Qwen3-ASR — Just dropped TODAY! 52 languages, <8% WER, SOTA open-source ASR
Qwen-Image — #1 open-source image model on AI Arena
All Apache 2.0. The most complete open-source AI stack, period.
So, what do you think now, what next release could be? an Language Model?
Comment below
- 1 reply
Awesome!
reacted to consome2's post with ❤️ about 2 months ago
Post
5245
We’ve released two conversational speech datasets from oto on Hugging Face 🤗
Both are based on real, casual, full-duplex conversations, but with slightly different focuses.
Dataset 1: Processed / curated subset
otoearth/otoSpeech-full-duplex-processed-141h
* Full-duplex, spontaneous multi-speaker conversations
* Participants filtered for high audio quality
* PII removal and audio enhancement applied
* Designed for training and benchmarking S2S or dialogue models
Dataset 2: Larger raw(er) release
otoearth/otoSpeech-full-duplex-280h
* Same collection pipeline, with broader coverage
* More diversity in speakers, accents, and conversation styles
* Useful for analysis, filtering, or custom preprocessing experiments
We intentionally split the release to support different research workflows:
clean and ready-to-use vs. more exploratory and research-oriented use.
The datasets are currently private, but we’re happy to approve access requests — feel free to request access if you’re interested.
If you’re working on speech-to-speech (S2S) models or are curious about full-duplex conversational data, we’d love to discuss and exchange ideas together.
Feedback and ideas are very welcome!
Both are based on real, casual, full-duplex conversations, but with slightly different focuses.
Dataset 1: Processed / curated subset
otoearth/otoSpeech-full-duplex-processed-141h
* Full-duplex, spontaneous multi-speaker conversations
* Participants filtered for high audio quality
* PII removal and audio enhancement applied
* Designed for training and benchmarking S2S or dialogue models
Dataset 2: Larger raw(er) release
otoearth/otoSpeech-full-duplex-280h
* Same collection pipeline, with broader coverage
* More diversity in speakers, accents, and conversation styles
* Useful for analysis, filtering, or custom preprocessing experiments
We intentionally split the release to support different research workflows:
clean and ready-to-use vs. more exploratory and research-oriented use.
The datasets are currently private, but we’re happy to approve access requests — feel free to request access if you’re interested.
If you’re working on speech-to-speech (S2S) models or are curious about full-duplex conversational data, we’d love to discuss and exchange ideas together.
Feedback and ideas are very welcome!
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- 2 replies
reacted to Reubencf's post with 🤗 about 2 months ago
Post
1897
Now Live: The Reubencf/Nano_Banana_Editor now includes 10 free requests/day! 🍌 I'm personally sponsoring these credits to help make open AI accessible to all.
(Note: Limits are subject to change based on funding).
Enjoy !
(Note: Limits are subject to change based on funding).
Enjoy !
replied to their post about 2 months ago
Awesome!
liked a Space about 2 months ago
replied to their post about 2 months ago
Do we need to add Qwen TTS?
posted an
update about 2 months ago
Post
2137
My Favorite Open Source Models for Jan 2026
1. General Use - deepseek-ai/DeepSeek-V3.2
2. Reasoning - deepseek-ai/DeepSeek-V3.2-Speciale
3. Coding - Qwen/Qwen3-Coder-30B-A3B-Instruct
4. OCR - Qwen/Qwen3-VL-8B-Instruct
5. Image Generation - black-forest-labs/FLUX.2-dev
6. Image Editing - Qwen/Qwen-Image-Edit-2509
What model do you use regularly?
1. General Use - deepseek-ai/DeepSeek-V3.2
2. Reasoning - deepseek-ai/DeepSeek-V3.2-Speciale
3. Coding - Qwen/Qwen3-Coder-30B-A3B-Instruct
4. OCR - Qwen/Qwen3-VL-8B-Instruct
5. Image Generation - black-forest-labs/FLUX.2-dev
6. Image Editing - Qwen/Qwen-Image-Edit-2509
What model do you use regularly?
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- 4 replies
published a Space about 2 months ago
What data used for Fine Tuning?
#1 opened about 2 months ago
by
mahimairaja
posted an
update about 2 months ago
Post
1507
Lacking vllm support for Transformers v5, frustrating only me?
updated a model about 2 months ago
published a model about 2 months ago