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AI Models 84757

• rorshark-vit-base↗

  amunchet

  This 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

• Llama3-1B-Base↗

  andrijdavid

• PULI-LlumiX-32K-instruct-GGUF↗

  ariel-ml

• pythia-14m-dd-rus-draft↗

  ArtyomSubDiv

• FrogNano-4B-2609-GGUF↗

  bartowski

  **Model details:** - Parameter count: 5B (source checkpoint) - Input support: text, image (with mmproj file) - details - Speculative decoding: yes (MTP) - details - imatrix: yes - details **Don't know which to choose?** Grab Q4_K_M (2.80GB) - usually a good mix of size and performance. Download instructions available here These quants run with llama.cpp - installable in one line via llama.app:

• Hermes-3-Llama-3.2-3B-GGUF↗

  bartowski

  All quants made using imatrix option with dataset from here Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run:

• Llama-3-Patronus-Lynx-8B-Instruct-GGUF↗

  bartowski

• nex-agi_Nex-N2-mini-GGUF↗

  bartowski

  Some of these quants (Q3_K_XL, Q4_K_L etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (nex-agi_Nex-N2-mini-Q8_0) or download them all in place (./)

• Steelskull_L3.3-Damascus-R1-GGUF↗

  bartowski

• XYZAILab_XYZ-Aquila-mini-GGUF↗

  bartowski

  All quants made using imatrix option with dataset from here - llama.cpp - ramalama - LM Studio - koboldcpp - Jan AI - Text Generation Web UI - LoLLMs - Atomic Chat Note: if it's a newly supported model, you may need to wait for an update from the developers.