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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗faster-whisper-small-multi-int8
ammaraldirawi基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗SAM3DBody-cpp-onnx-models
AmmarkoV基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗wav2vec2-large-xlsr-kn
amoghsgopadiFine-tuned facebook/wav2vec2-large-xlsr-53 on Kannada using the OpenSLR SLR79 dataset. When using this model, make sure that your speech input is sampled at 16kHz. The model can be used directly (without a language model) as follows, assuming you have a dataset with Kannada `sentence` and `path` fields: The colab notebook used for training can be found here.
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗MaskGCT
amphion基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗FinABSA
amphora基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗KorFinASC-XLM-RoBERTa
amphora基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗real-nepali-v0.2-kala
ampixa基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗sanoTTS
ampixa***sano*** (सानो) — Nepali for **"small."** A family of tiny neural text-to-speech voices — **294k to 2.27M parameters** — that run with **no cloud and no NPU**: real-time on a ~$3 ESP32-S3 (out a GPIO into an LM386 and a speaker), or live in the browser via WASM. **Live demo:** tts.ampixa.com/sanoTTS — every voice synthesizes your text live in the browser, no server, no upload. Python needs `sanotts` >= 0.3.0, the browser `sanotts-web` >= 0.3.0. Both fall back to the GitHub releases or the Pages host if Hugging Face cannot be reached, so an outage here cannot break an install. Python packages land in `~/.cache/sanotts/`; set `SANOTTS_VOICE_SOURCE=hf` or `=github` to pin one host. In the browser, passing `voiceBase` yourself turns the fallback off, so a self-hosted deployment never quietly reaches back to our servers.
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View details ↗PoC-demo
Amritemperor123基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Fine-tuned facebook/wav2vec2-large-xlsr-53 in Tamil using the Common Voice When using this model, make sure that your speech input is sampled at 16kHz.
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View details ↗watermark_detector
amrul-hzzThis model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6014 - Accuracy: 0.6574 The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3
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View details ↗llama-cpp-python-wheels
amukhinfly基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗rorshark-vit-base
amunchetThis model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0393 - Accuracy: 0.9923 The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 1337 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5.0 - Transformers 4.36.0.dev0 - Pytorch 2.1.1+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0
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View details ↗LawToken-7B-a2
amy011872基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Hemmingway-1-Unlocked-GGUF
amylynn基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.8-27B-TURBO-NInfer
amynporb基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗decima-small
amyrmahdy基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗finqa_model
anablasi基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗gemma-4-E2B-it-uncensored-GGUF
Anachronox39基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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