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AI 模型 535
- EmoWhisper-AnS-Small-v0.1↗
mkrausio
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- faster-whisper-medium↗
Systran
This repository contains the conversion of openai/whisper-medium to the CTranslate2 model format. This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper. Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the `compute_type` option in CTranslate2.
- whisper-ja-anime-v0.3↗
efwkjn
- balochi-whisper-medium↗
shehzadkhalid04
- whisper-tiny-lv↗
RaivisDejus
- whisper-medium-jp↗
vumichien
This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.3029 - Wer: 9.0355 The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP
- whisper-large-v3-turkish-general↗
turkmedstt
- whisper-small.en_timestamped↗
onnx-community
https://huggingface.co/openai/whisper-small.en with ONNX weights to be compatible with Transformers.js. Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
- azuolas-whisper-lt↗
akisviete
- bengali-whisper-medium-ct2↗
SayedShaun