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AI モデル 84759
- doosra-qwen3.5-4b-toolcalls-b-step350↗
Sarthak213
- chinese-alpaca-2-13b-gguf↗
shaowenchen
- DeepDataDemon-8B-GGUF↗
SleepyReLU
- resnet101.imagenet↗
smp-hub
- stablelm-2-12b↗
Stability AI
- py313-pylingual-v3-statement↗
syssec-utd
This model is a fine-tuned version of Salesforce/codet5-base on the syssec-utd/statement-py313-pylingual-v3-tokenized dataset. The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 24 - eval_batch_size: 24 - 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
- gra5↗
tao1000
- MistoLine↗
TheMistoAI
**We are thrilled to announce that MistoLine has officially surpassed 300,000 total downloads!** 🚀 (Verified via official Hugging Face API) MistoLine also achieved **#1 in the Text-to-Image Trending list** and **Top 4 Overall** on Hugging Face! These milestones reflect the incredible support and adoption from the open-source AI community. Check out our trending highlights: MistoLine is an SDXL-ControlNet model that can adapt to any type of line art input, demonstrating high accuracy and excellent stability. It can generate high-quality images (with a short side greater than 1024px) based on user-provided line art of various types, including hand-drawn sketches, different ControlNet line preprocessors, and model-generated outlines. MistoLine eliminates the need to select different ControlNet models for different line preprocessors, as it exhibits strong generalization capabilities across diverse line art conditions.
- VLM2Vec-LoRA↗
TIGER-Lab
- Gemma-4-E4B-it-qat-q4_0-unquantized-abliterated-GGUF↗
timfromhcs