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AI モデル 85003

• Qwen3.8-9B-Distill-MLX-6bit↗

  RolanDorisTech

• Qwen3.6-35B-A3B-NVFP4↗

  sakamakismile

• aesthetics-predictor-v1-vit-base-patch16↗

  shunk031

• mamba-370m-hf↗

  state-spaces

• gte-small↗

  Supabase

  _Fork of https://huggingface.co/thenlper/gte-small with ONNX weights to be compatible with Transformers.js. See JavaScript usage._ The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE-large, GTE-base, and GTE-small. The GTE models are trained on a large-scale corpus of relevance text pairs, covering a wide range of domains and scenarios. This enables the GTE models to be applied to various downstream tasks of text embeddings, including **information retrieval**, **semantic textual similarity**, **text reranking**, etc. Performance of GTE models were compared with other popular text embedding models on the MTEB benchmark. For more detailed comparison results, please refer to the MTEB leaderboard.

• py313-pylingual-v3-segmenter↗

  syssec-utd

  This model is a fine-tuned version of syssec-utd/py313-pylingual-v3-mlm on the syssec-utd/segmentation-py313-pylingual-v3-tokenized dataset. It achieves the following results on the evaluation set: - Loss: 0.0047 - Precision: 0.9945 - Recall: 0.9944 - F1: 0.9945 - Accuracy: 0.9983 The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 28 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 2 - mixed_precision_training: Native AMP

• tf_efficientnet_b1.ns_jft_in1k↗

  timm

  A EfficientNet image classification model. Trained on ImageNet-1k and unlabeled JFT-300m using Noisy Student semi-supervised learning in Tensorflow by paper authors, ported to PyTorch by Ross Wightman.

• MiniCPM5-1B-Uncensored-GGUF↗

  tinyopsec

• codellama-7b-bnb-4bit↗

  unsloth

• gemma-1.1-2b-it-bnb-4bit↗

  unsloth