Lightonai
Models by this creator
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alfred-40b-0723
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alfred-40b-0723 is a finetuned version of the Falcon-40B model, developed by LightOn. It was obtained through Reinforcement Learning from Human Feedback (RLHF) and is the first in a series of RLHF models based on Falcon-40B that will be regularly released. The model is available under the Apache 2.0 License. Model inputs and outputs alfred-40b-0723 can be used as an instruct or chat model. The prefix to use Alfred in chat mode is: Alfred is a large language model trained by LightOn. Knowledge cutoff: November 2022. Current date: 31 July, 2023 User: {user query} Alfred: The stop word User: should be used. Inputs User queries**: Natural language prompts or instructions for the model to respond to. Outputs Text responses**: The model generates text responses to the user's input, which can be used for tasks like open-ended conversation, question answering, text generation, and more. Capabilities alfred-40b-0723 is capable of understanding and generating text in English, German, Spanish, French, and to a limited extent in Italian, Portuguese, Polish, Dutch, Romanian, Czech, and Swedish. It can engage in open-ended dialogue, provide informative responses, and generate creative content. What can I use it for? The alfred-40b-0723 model can be used for a variety of research and development purposes, such as exploring the capabilities of large language models trained with RLHF, building conversational AI assistants, and generating text for creative or analytical tasks. However, the model should not be used in production without adequate assessment of risks and mitigation, or for any use cases that may be considered irresponsible or harmful. Things to try Since alfred-40b-0723 is a finetuned version of Falcon-40B, you can experiment with prompts and tasks that leverage its specialized training, such as engaging in more natural, open-ended dialogue or providing responses that demonstrate increased alignment with human preferences and values. Additionally, you can compare the performance of alfred-40b-0723 to the original Falcon-40B model to better understand the impact of the RLHF finetuning process.
Updated 9/6/2024
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alfred-40b-1023
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alfred-40b-1023 is a finetuned version of the Falcon-40B language model, developed by LightOn. It has an extended context length of 8192 tokens, allowing it to process longer inputs compared to the original Falcon-40B model. alfred-40b-1023 is similar to other finetuned models based on Falcon-40B, such as alfred-40b-0723, which was finetuned with Reinforcement Learning from Human Feedback (RLHF). However, alfred-40b-1023 focuses on increasing the context length rather than using RLHF. Model inputs and outputs Inputs User prompts**: alfred-40b-1023 can accept various types of user prompts, including chat messages, instructions, and few-shot prompts. Context tokens**: The model can process input sequences of up to 8192 tokens, allowing it to work with longer contexts compared to the original Falcon-40B. Outputs Text generation**: alfred-40b-1023 can generate relevant and coherent text in response to the user's prompts, leveraging the extended context length. Dialogue**: The model can engage in chat-like conversations, with the ability to maintain context and continuity across multiple turns. Capabilities alfred-40b-1023 is capable of handling a wide range of tasks, such as text generation, question answering, and summarization. Its extended context length enables it to perform particularly well on tasks that require processing and understanding of longer input sequences, such as topic retrieval, line retrieval, and multi-passage question answering. What can I use it for? alfred-40b-1023 can be useful for applications that involve generating or understanding longer text, such as: Chatbots and virtual assistants**: The model's ability to maintain context and engage in coherent dialogue makes it suitable for building interactive conversational agents. Summarization and information retrieval**: The extended context length allows the model to better understand and summarize long-form content, such as research papers or technical documentation. Multi-document processing**: alfred-40b-1023 can be used to perform tasks that require integrating information from multiple sources, like question answering over long passages. Things to try One interesting aspect of alfred-40b-1023 is its potential to handle more complex and nuanced prompts due to the extended context length. For example, you could try providing the model with multi-part prompts that build on previous context, or prompts that require reasoning across longer input sequences. Experimenting with these types of prompts can help uncover the model's strengths and limitations in dealing with more sophisticated language understanding tasks.
Updated 9/6/2024