VaultGemma is a lightweight language model pre-trained by Google based on differential privacy technology, with powerful privacy protection capabilities. It uses differential privacy stochastic gradient descent (DP-SGD) for pre-training, providing mathematical privacy guarantees for the training data. It has less than 1 billion parameters and is suitable for a variety of natural language processing tasks.

Natural Language ProcessingTransformers

Realism Illustrious is a text-to-image generation model based on Stable Diffusion XL, specifically optimized for generating images in anime and realistic styles. This model excels in character details, color gradient, and dynamic range, capable of generating high-quality visual content.

Computer VisionDiffusersEnglish

A pre-trained language model fusion quantized GGUF file set created based on mergekit, using asymmetric gradient SLERP method to fuse two 12B parameter models, suitable for text generation tasks.

Natural Language ProcessingTransformers

A LoRA adapter specifically designed for the FLUX model, infusing generated works with a modern minimalist illustration style, featuring warm and soft color schemes, delicate gradient effects, and grainy texture.

Computer VisionDiffusers

This is a GGUF quantized version based on the Meta Llama-3-70B-Instruct model, developed by GradientAI, supporting an ultra-long context length of 1048k. The model has been optimized through instruction fine-tuning and is suitable for various natural language processing tasks. It also offers multiple quantization levels to meet different hardware requirements.

Natural Language ProcessingGgufEnglish

Flux LoRA model for creating precise color gradient effects, trained on public domain images.

Computer VisionDiffusersOther

An extended long-context model based on Meta-Llama-3-8B-Instruct, achieving 4194K context length support through RoPE theta parameter adjustment

Natural Language ProcessingTransformersEnglish

An extended version of Llama-3 8B for long-context processing developed by Gradient, supporting context lengths exceeding 1 million tokens through optimized RoPE theta parameters for efficient long-text handling.

Natural Language ProcessingTransformersEnglish

A long-context model extended from Meta-Llama-3-8B-Instruct, supporting 262k tokens context length

Natural Language ProcessingTransformersEnglish

This is a fixed version of the Llama 3 8B base model that resolves the NaN gradient issue caused by zero weights in special tokens in the original model.

Natural Language ProcessingTransformers

CatPPT is a high-performance 7B chat model that fuses the openchat and neuralchat models through the Gradient SLERP method. It performs excellently on the leaderboard and has no evaluation data pollution.

Natural Language ProcessingTransformers

CodeBooga-34B-v0.1 is a large-scale code generation model created by merging Phind-CodeLlama-34B-v2 and WizardCoder-Python-34B-V1.0 using the BlockMerge Gradient script, focusing on code generation tasks.

Natural Language ProcessingTransformers

TwinBooster is a DeBERTa V3 base model fine-tuned on the PubChem bioassay corpus, combining Barlow Twins self-supervised learning method and gradient boosting techniques to enhance molecular property prediction.

Scientific ComputingTransformersEnglish

This is an NLP model implemented based on PyTorch, combining a language model and prediction head with support for gradient backpropagation.

Natural Language ProcessingTransformersEnglish

A gradient boosted tree model based on TensorFlow for binary classification tasks with structured data.

Scientific ComputingTensorflow

ResNet-18 image classification model pre-trained on the ImageNette dataset, using skip connections to address gradient propagation issues in deep networks

Computer VisionTransformers

mDeBERTa is the multilingual version of DeBERTa, employing ELECTRA-style pretraining and gradient-disentangled embedding sharing technology, demonstrating excellent performance in cross-lingual tasks like XNLI

Natural Language ProcessingTransformersMultiple Languages

ResNet152 is an image classification model based on deep residual learning, which solves the gradient vanishing problem in deep network training through residual connections.

Computer VisionTransformers

DeBERTa-v3 is an improved natural language understanding model developed by Microsoft, optimized through ELECTRA-style pretraining and gradient-disentangled embedding sharing technology to achieve efficient performance while maintaining a relatively small parameter count.

Natural Language ProcessingTransformersEnglish

DeBERTaV3 is an improved version of the DeBERTa model proposed by Microsoft, which enhances efficiency through ELECTRA-style gradient-disentangled embedding sharing pretraining method, demonstrating excellent performance in natural language understanding tasks.

Natural Language ProcessingTransformersEnglish