Ziyue-GPT2
binxu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 ↗DISCOVER & COMPARE
Explore AI models 84991
g4mer
Biociphers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 ↗distill-whisper-th-large-v3
biodatlab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 ↗distill-whisper-th-small
biodatlab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 ↗ThonburianTTS
biodatlab**Thonburian TTS** is a **Thai Text-to-Speech (TTS)** engine built on top of the F5-TTS. It generates **natural and expressive Thai speech** by leveraging **Flow-Matching diffusion techniques** and can **mimic reference voices** from short audio samples. The system supports: The **models** are released under the Creative Commons Attribution Non-Commercial ShareAlike 4.0 License (CC BY-NC-SA 4.0). We would like to acknowledge NSTDA Supercomputer Center (ThaiSC) project \#pv824003 for providing computing resources for this work.
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View details ↗whisper-th-large-v3-combined
biodatlabThis model is a fine-tuned version of openai/whisper-medium on augmented versions of the mozilla-foundation/common_voice_13_0 th, google/fleurs, and curated datasets. It achieves the following results on the common-voice-13 test set: - WER: 6.59 (with Deepcut Tokenizer) The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 10000 - mixed_precision_training: Native AMP
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View details ↗whisper-th-medium-combined
biodatlabThis model is a fine-tuned version of openai/whisper-medium on augmented versions of the mozilla-foundation/common_voice_13_0 th, google/fleurs, and curated datasets. It achieves the following results on the common-voice-13 test set: - WER: 7.42 (with Deepcut Tokenizer) The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 10000 - mixed_precision_training: Native AMP
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View details ↗whisper-th-small-combined
biodatlab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 ↗bioelx_retriever
bioelx-nlp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 ↗bioformer-8L
bioformers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 ↗bioformer-8L-ncbi-disease
bioformers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 ↗esm3-sm-open-v1
biohub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 ↗ESMC-300M
biohubESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.
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View details ↗esmc-300m-2024-12
biohub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 ↗ESMC-300M-hf
biohubESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.
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View details ↗ESMC-300M-step1000k
biohub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 ↗ESMC-300M-step1500k
biohub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 ↗ESMC-300M-step250k
biohub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 ↗ESMC-300M-step500k
biohub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 ↗ESMC-300M-step750k
biohub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 ↗ESMC-600M
biohubESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.
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View details ↗esmc-600m-2024-12
biohub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 ↗ESMC-600M-hf
biohubESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.
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View details ↗ESMC-600M-step1000k
biohub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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