328 models available
MistralMinistral 8BWe introduce two new state-of-the-art models for local intelligence, on-device computing, and at-the-edge use cases. We call them les Ministraux: Ministral 3B and Ministral 8B.
BigCodeStarCoder2 7B- Project Website: bigcode-project.org - Paper: Link - Point of Contact: contact@bigcode-project.org - Languages: 17 Programming languages
GoogleGemma 2 9BGemma 2 9B is Google's mid-size open model built on Gemini research. Features improved reasoning and safety with a novel architecture optimized for efficient inference on consumer hardware.
IBMGranite 3.1 8BModel Summary: Granite-3.1-8B-Instruct is a 8B parameter long-context instruct model finetuned from Granite-3.1-8B-Base using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets tailored for solving long context problems. This model is developed using a diverse set of techniques with a structured chat format, including supervised finetuning, model alignment using reinforcement learning, and model merging.
LLaVALLaVA 1.5 7BModel type: LLaVA is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture.
Cognitive ComputationsSamantha 7BSamantha has been trained in philosophy, psychology, and personal relationships.
MistralMinistral 3 3BThe smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
MicrosoftPhi 4 Mini 4BPhi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. The model belongs to the Phi-4 model family and supports 128K token context length. The model underwent an enhancement process, incorporating both supervised fine-tuning and direct preference optimization to support precise instruction adherence and robust safety measures.
AlibabaQwen 2.5 7BQwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
MetaCodeLlama 7B InstructCode Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the 7B instruct-tuned version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. Links to other models can be found in the index at the bottom.
MosaicMLMPT-7B-InstructMPT-7B Instruct is MosaicML's instruction-tuned model with a commercially permissive license. Supports 65K context with ALiBi positional encoding for efficient long-document processing.
Stability AIStableLM 2 12B`Stable LM 2 12B Chat` is a 12 billion parameter instruction tuned language model trained on a mix of publicly available datasets and synthetic datasets, utilizing Direct Preference Optimization (DPO).
DeepSeekDeepSeek LLM 7BIntroducing DeepSeek LLM, an advanced language model comprising 7 billion parameters. It has been trained from scratch on a vast dataset of 2 trillion tokens in both English and Chinese. In order to foster research, we have made DeepSeek LLM 7B/67B Base and DeepSeek LLM 7B/67B Chat open source for the research community.
DeepSeekDeepSeek R1 1.5BDeepSeek R1 Distill Qwen 1.5B is a compact reasoning model distilled from DeepSeek-R1, based on Qwen2.5-Math-1.5B. Fine-tuned on 800K curated samples, it achieves 83.9% on MATH-500 and supports chain-of-thought reasoning on resource-constrained devices.
MetaLlama 3.1 8BLlama 3.1 8B is Meta's efficient general-purpose model supporting 128K context and multilingual text generation. Optimized for dialogue, summarization, reasoning, and code generation tasks.
01.AI
Cerebras