• Alpaca - The current Alpaca model is fine-tuned from a 7B LLaMA model [1] on 52K instruction-following data generated by the techniques in the Self-Instruct [2] paper, with some modifications that we discuss in the next section.
• BELLE - BELLE is more concerned with how to build on the foundation of open-source pre-trained large language models to help everyone obtain their own high-performing, instruction-driven language model, thereby lowering the barriers to research and application of large language models, especially Chinese ones.
• Bloom - The BLOOM model has been proposed with its various versions through the BigScience Workshop. BigScience is inspired by other open science initiatives where researchers have pooled their time and resources to collectively achieve a higher impact.
• dolly - dolly-v2-12b is a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA)
• Falcon 40B - Falcon-40B-Instruct is a 40B parameters causal decoder-only model built by TII based on Falcon-40B and finetuned on a mixture of Baize. It is made available under the Apache 2.0 license.
• FastChat - FastChat is an open platform for training, serving, and evaluating large language model-based chatbots. The core features include:
• Gorilla LLM - Gorilla is a LLM that can provide appropriate API calls. It is trained on three massive machine learning hub datasets: Torch Hub, TensorFlow Hub and HuggingFace.
• GLM-6B (ChatGLM) - ChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters.
• GLM-130B (ChatGLM) - GLM-130B is an open bilingual (English & Chinese) bidirectional dense model with 130 billion parameters, pre-trained using the algorithm of General Language Model (GLM). It is designed to support inference tasks with the 130B parameters on a single A100 (40G * 8) or V100 (32G * 8) server.
• GPT-NeoX - GPT-NeoX-20B, a 20 billion parameter autoregressive language model trained on the Pile, whose weights will be made freely and openly available to the public through a permissive license.
• MPT-7B - MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B.
• PaLM 2 - PaLM 2 is a state-of-the-art language model with improved multilingual, reasoning and coding capabilities.
• StableLM - Stability AI released a new open-source language model, StableLM. The Alpha version of the model is available in 3 billion and 7 billion parameters, with 15 billion to 65 billion parameter models to follow.
• Starcoder - StarCoder is Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks.

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