Skip to main content

Open Source ChatGPT alternatives

If you are looking for open source chat gpt alternatives, you might be interested in this blog post. In this post, I will introduce you to eight open source projects that aim to provide chatbot functionality using natural language generation models similar to ChatGPT. ChatGPT is a powerful and popular chatbot that can do all sorts of things, but it is not the only example of its kind. Here are some alternatives you might want to try instead.


1. LLaMA

The LLaMA project encompasses a set of foundational language models that vary in size from 7 billion to 65 billion parameters. These models are trained on a large and diverse corpus of text, and can generate coherent and fluent text on various topics and domains. LLaMA also provides a web interface where you can interact with the models and test their capabilities.


2. Alpaca

Stanford Alpaca claims that it can compete with ChatGPT and anyone can reproduce it in less than 600$. Alpaca is based on a smaller model called GPT-2, which is fine-tuned on a dataset of Reddit conversations. Alpaca can generate engaging and diverse responses to user queries, and can also handle multiple turns of dialogue.


3. Vicuna

Vicuna is another project that uses GPT-2 as a base model and fine-tunes it on various datasets of human conversations. Vicuna can generate responses that are relevant, informative, and consistent with the dialogue context. Vicuna also supports different modes of interaction, such as casual chat, trivia quiz, and storytelling.


4. OpenChatKit

OpenChatKit is a framework that allows you to build your own chatbot using any natural language generation model. OpenChatKit provides a simple and flexible API that lets you plug in your model, define your dialogue logic, and customise your user interface. OpenChatKit also comes with some pre-built chatbots that use GPT-3 Playground as the underlying model.


5. GPT4ALL

GPT4ALL is a platform that enables anyone to create and share chatbots using GPT-3 or GPT-Neo models. GPT4ALL allows you to specify your chatbot's personality, domain, and style, and then generate responses based on your input. You can also browse and interact with other chatbots created by the community.


6. Raven RWKV

Raven RWKV is a chatbot that uses GPT-3 to generate responses that are witty, humorous, and creative. Raven RWKV stands for "Raven Randomly Writes Kooky Verses' ', and it can produce poems, jokes, stories, and more based on your input. Raven RWKV can also engage in casual conversation and answer questions about itself.


7. OPT

OPT is a chatbot that uses GPT-3 to generate responses that are optimised for a specific objective or metric. OPT can help you improve your writing skills, boost your productivity, or achieve your goals by providing feedback, suggestions, or encouragement based on your input. OPT can also generate content such as headlines, summaries, or slogans.


8. Flan-T5-XXL

Flan-T5-XXL is a chatbot that uses T5-XXL as the underlying model. T5-XXL is a large-scale natural language generation model that can perform various tasks such as summarization, translation, question answering, and text simplification. Flan-T5-XXL can generate responses that are informative, coherent, and diverse based on your input.


These are some of the open source chat gpt alternatives that you can try out for yourself. Each of them has its own strengths and weaknesses, and you might find some of them more suitable for your needs than others. I hope this blog post has given you some insights into the current state of the art in natural language generation and chatbot technology.


Comments

Popular posts from this blog

OpenAI's NSA Appointment Raises Alarming Surveillance Concerns

  The recent appointment of General Paul Nakasone, former head of the National Security Agency (NSA), to OpenAI's board of directors has sparked widespread outrage and concern among privacy advocates and tech enthusiasts alike. Nakasone, who led the NSA from 2018 to 2023, will join OpenAI's Safety and Security Committee, tasked with enhancing AI's role in cybersecurity. However, this move has raised significant red flags, particularly given the NSA's history of mass surveillance and data collection without warrants. Critics, including Edward Snowden, have voiced their concerns that OpenAI's AI capabilities could be leveraged to strengthen the NSA's snooping network, further eroding individual privacy. Snowden has gone so far as to label the appointment a "willful, calculated betrayal of the rights of every person on Earth." The tech community is rightly alarmed, with many drawing parallels to dystopian fiction. The move has also raised questions about ...

What is happening inside of the black box?

  Neel Nanda is involved in Mechanistic Interpretability research at DeepMind, formerly of AnthropicAI, what's fascinating about the research conducted by Nanda is he gets to peer into the Black Box to figure out how different types of AI models work. Anyone concerned with AI should understand how important this is. In this video Nanda discusses some of his findings, including 'induction heads', which turn out to have some vital properties.  Induction heads are a type of attention head that allows a language model to learn long-range dependencies in text. They do this by using a simple algorithm to complete token sequences like [A][B] ... [A] -> [B]. For example, if a model is given the sequence "The cat sat on the mat," it can use induction heads to predict that the word "mat" will be followed by the word "the". Induction heads were first discovered in 2022 by a team of researchers at OpenAI. They found that induction heads were present in ...

Prompt Engineering: Expert Tips for a variety of Platforms

  Prompt engineering has become a crucial aspect of harnessing the full potential of AI language models. Both Google and Anthropic have recently released comprehensive guides to help users optimise their prompts for better interactions with their AI tools. What follows is a quick overview of tips drawn from these documents. And to think just a year ago there were countless YouTube videos that were promoting 'Prompt Engineering' as a job that could earn megabucks... The main providers of these 'chatbots' will hopefully get rid of this problem, soon. Currently their interfaces are akin to 1970's command lines, we've seen a regression in UI. Constructing complex prompts should be relegated to Linux lovers. Just a word of caution, even excellent prompts don't stop LLM 'hallucinations'. They can be mitigated against by supplementing a LLM with a RAG, and perhaps by 'Memory Tuning ' as suggested by Lamini (I've not tested this approach yet).  ...