This is a lightweight text generation model based on the Meta LLaMA 3 8B model. It is efficiently fine-tuned using the Unsloth framework and converted to the GGUF format. The model is optimized for the Alpaca dataset, suitable for local deployment and inference, especially in resource-constrained environments.

Natural Language ProcessingGguf

SAM 3 is the third-generation promptable segmentation foundation model launched by Meta, which uniformly supports image and video segmentation tasks. Compared with its predecessor SAM 2, it introduces the ability of open vocabulary concept segmentation, can handle a large number of text prompts, and achieves 75-80% of human performance in the SA-CO benchmark test.

Computer VisionTransformersEnglish

This is an optimized version based on the original DeepSeek-OCR model, specifically an OCR model that supports inference on Apple Metal Performance Shaders (MPS) and CPU. It can extract text from images and convert it into a structured format, supporting multilingual document recognition.

MultimodalTransformersOther

This model is a large language model fine-tuned on a specific dataset based on meta-llama/Llama-3.1-70B-Instruct. It is specifically designed for text generation tasks and achieved a loss value of 0.6542 on the evaluation set.

Natural Language ProcessingPeft

This is a text generation model fine-tuned based on the Google Gemma-3-4B-IT model, specifically designed to generate diverse and relevant search queries according to the metadata of demo templates. This model uses the LoRA adapter for efficient fine-tuning and is a key component of the structured document field adaptive dense retrieval framework.

Natural Language ProcessingSafetensorsEnglish

This model is a fine-tuned version based on meta-llama/Llama-3.3-70B-Instruct. It is trained using the mlabonne/FineTome-100k dataset, which contains 100k token data. The model is fine-tuned using the Unsloth and Huggingface TRL libraries and supports English language processing.

Natural Language ProcessingTransformersEnglish

SAM 3 is the third - generation promptable segmentation foundation model launched by Meta. It can use text or visual prompts (points, boxes, masks) to detect, segment, and track objects in images and videos. Compared with previous generations, SAM 3 introduces the ability to exhaustively segment all instances of open - vocabulary concepts, supports a large number of open - vocabulary prompts, and achieves 75 - 80% of human performance on the SA - CO benchmark.

Computer VisionTransformersEnglish

This model is a text generation model fine-tuned based on Meta's Llama-3.1 architecture. It is trained using reinforcement learning with the TRL library and the GRPO (Group Relative Policy Optimization) method, and is specifically optimized for argument generation tasks.

Natural Language ProcessingTransformers

Wraith-8B is the first model in the VANTA Research entity series, fine-tuned based on Meta's Llama 3.1 8B Instruct. This model performs excellently in mathematical reasoning, achieving an accuracy rate of 70% in the GSM8K benchmark test. It also has a unique cosmic intelligence perspective, providing strong support for various application scenarios.

Natural Language ProcessingTransformersEnglish

Llama-4-Maverick-17B-128E-Instruct-NVFP4 is a multilingual large language model that has undergone FP4 quantization processing. It is based on the Meta-Llama-3.1 architecture and is specifically designed for business and research purposes. By quantizing the weights and activations to the FP4 data type, this model significantly reduces the disk space and GPU memory requirements while maintaining good performance.

Natural Language ProcessingSafetensorsMultiple Languages

metatune-gpt20b is a large language model prototype with self-improvement ability. It can generate new data for itself, evaluate its own performance, and adjust hyperparameters according to improvement indicators. This model performs excellently in scientific and mathematical understanding at the postdoctoral level and can also be used for coding tasks.

Natural Language ProcessingTransformersEnglish

This is the FP8 quantized version of the Meta Llama-3.1-8B-Instruct model. By performing FP8 quantization on weights and activation values, it significantly reduces the disk size and GPU memory requirements while maintaining good model performance.

Natural Language ProcessingSafetensors

Llama-3.1-8B-onnx-ryzenai-npu is an optimized version developed by AMD based on Meta's Llama-3.1-8B model, specifically optimized for deployment on the AMD Ryzen AI NPU. Through Quark quantization, OGA model builder, and NPU-specific post-processing technology, this model significantly improves the inference efficiency on AMD hardware while maintaining high-quality text generation capabilities.

Natural Language ProcessingOnnxEnglish

This model is the 8-billion parameter version in the Llama 3.1 series released by Meta. It has been processed and post-processed by the AMD Quark quantization tool, optimizing the deployment and inference efficiency on specific hardware. It is a multilingual text generation model that supports multiple languages and performs excellently in benchmark tests such as MMLU.

Natural Language ProcessingOnnxMultiple Languages

MEDFIT-LLM-3B is a language model specifically optimized for medical Q&A, fine-tuned based on Meta's Llama-3.2-3B-Instruct. This model is trained on medical datasets using LoRA technology, significantly improving its understanding and direct answering abilities in the medical field. It is suitable for applications such as medical chatbots and patient education.

Natural Language ProcessingTransformersEnglish

MobileLLM-Pro is a 1-billion-parameter efficient device-side language model launched by Meta, optimized for mobile devices, supporting a context length of 128k and providing high-quality inference capabilities. This model is trained using knowledge distillation technology, outperforming models of the same scale in multiple benchmark tests, and supporting nearly lossless 4-bit quantization.

Natural Language ProcessingTransformersEnglish

MobileLLM-R1 is an efficient inference model series released by Meta, including three scales of 140M, 360M, and 950M. This model is specifically optimized for mathematical, programming, and scientific problems, achieving comparable or even better performance than large-scale models with a smaller parameter scale.

Natural Language ProcessingTransformersEnglish

MobileLLM-R1 is a series of efficient inference language models released by Meta, focusing on solving mathematical, programming, and scientific problems. This model can still achieve excellent performance with a relatively small parameter scale, and provides a complete training recipe and data sources to support reproducible research.

Natural Language ProcessingTransformersEnglish

MobileLLM-R1 is a series of efficient reasoning models launched by Meta, focusing on solving mathematical, programming, and scientific problems. The model offers three scale versions of 140M, 360M, and 950M, with excellent reasoning ability and reproducibility.

Natural Language ProcessingTransformersEnglish

Llama-3.1-Nemotron-Safety-Guard-8B-v3 is a multilingual content security review model developed by NVIDIA. It is optimized based on Meta's Llama-3.1-8B-Instruct model and is specifically designed to detect and classify unsafe content in human-LLM interactions.

Natural Language ProcessingSafetensorsMultiple Languages