100+ Open-source LLMs Ready to Use

BioMistral is a suite of Mistral-based further pre-trained open source models suited for the medical domains and pre-trained using textual data from PubMed Central Open Access. This is the base 7B model.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 7B base version.

Code 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 7B instruct-tuned version.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 7B Python specialist version.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 13B base version.

Code 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 instruction-tuned 13B model.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 34B base version.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 13B Python specialist version.

Code 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 34B instruct-tuned version.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 34B Python specialist version.

Fine-tuned CodeLlama-34B and CodeLlama-34B-Python on an internal Phind dataset.

Fine-tuned CodeLlama-34B and CodeLlama-34B-Python on an internal Phind dataset.

Fine-tuned Phind-CodeLlama-34B-v1 on an additional 1.5B tokens high-quality programming-related data.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 70B base version.

Code 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 instruction-tuned 70B model.

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 70B Python specialist version.

This is the 2B base version of the Gemma model.

This is the 2B instruction-tuned version of the Gemma model.

This is the 7B base version of the Gemma model

This is the 7B instruction-tuned version of the Gemma model.

Google's latest iteration of open LLMs, based on Google Deepmind Gemini

Google's latest iteration of open LLMs, based on Google Deepmind Gemini

Google's latest iteration of open LLMs, based on Google Deepmind Gemini

Google's latest iteration of open LLMs, based on Google Deepmind Gemini

GPT-2 is a transformers model pretrained on a very large corpus of English data in a self-supervised fashion.

GPT-2 Medium is the 355M parameter version of GPT-2, a transformer-based language model created and released by OpenAI.

GPT-2 Large is the 774M parameter version of GPT-2, a transformer-based language model created and released by OpenAI.

GPT-2 XL is the 1.5B parameter version of GPT-2, a transformer-based language model created and released by OpenAI.

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the base 7B model.

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the instruction tuned 7B model.

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the base 13B model.

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the instruction-tuned 13B model.

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the base 70B model.

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the instruction-tuned 70B model.

Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. This is the base 8B parameter model.

Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. This is the instruction-tuned 8B parameter model.

Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. This is the base 70B parameter model.

Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. This is the instruction tuned 70B parameter model.

Meta Llama Guard 2 is an 8B parameter Llama 3-based [1] LLM safeguard model.

Meditron is a suite of open-source medical Large Language Models (LLMs). Meditron-7B is a 7 billion parameters model adapted to the medical domain from Llama-2-7B through continued pretraining on a comprehensively curated medical corpus, including selected PubMed articles, abstracts, a new dataset of internationally-recognized medical guidelines, and general domain data from RedPajama-v1.

Meditron is a suite of open-source medical Large Language Models (LLMs). Meditron-70B is a 70 billion parameters model adapted to the medical domain from Llama-2-70B through continued pretraining on a comprehensively curated medical corpus, including selected PubMed articles, abstracts, a new dataset of internationally-recognized medical guidelines, and general domain data from RedPajama-v1.

The Mixtral-8x7B-instruct-v0.1 Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.

The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.2.

The Mistral-7B-Instruct-v0.3 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.3.

The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters.

The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the Mistral-7B-v0.1 generative text model using a variety of publicly available conversation datasets.

The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts.

Phi-2 is a Transformer with 2.7 billion parameters. It was trained using the same data sources as Phi-1.5, augmented with a new data source that consists of various NLP synthetic texts and filtered websites (for safety and educational value).

The Phi-3-Mini-4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open model trained with the Phi-3 datasets. This is the 4k context window instruct version of the model.

Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. This is the 14B base version.

Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. This is the 32B base version.

Qwen1.5 is the beta version of Qwen2, a transformer-based decoder-only language model pretrained on a large amount of data. This is the 72B base version.

Qwen2 is a language model series including decoder language models of different model sizes, developed by Qwen team, Alibaba Cloud

Qwen2 is a language model series including decoder language models of different model sizes, developed by Qwen team, Alibaba Cloud

Qwen2 is a language model series including decoder language models of different model sizes, developed by Qwen team, Alibaba Cloud

Qwen2 is a language model series including decoder language models of different model sizes, developed by Qwen team, Alibaba Cloud

Upstage's Solar model is a family of large language models (LLMs) known for its compact yet powerful performance compared to similar sized models below 13B parameter size. The Solar Chat model is optimized for multi-turn chat purposes to effectively handle extended conversations, making it a compelling choice for interactive applications.

Zephyr-7B-β is the second model in the series, and is a fine-tuned version of mistralai/Mistral-7B-v0.1 that was trained on on a mix of publicly available, synthetic datasets using Direct Preference Optimization (DPO).