Mbzuai
Models by this creator
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LaMini-Flan-T5-783M
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The LaMini-Flan-T5-783M model is one of the LaMini-LM model series from MBZUAI. It is a fine-tuned version of the google/flan-t5-large model, which has been further trained on the LaMini-instruction dataset containing 2.58M samples. This model is part of a diverse collection of distilled models developed by MBZUAI, which also includes other versions based on T5, Flan-T5, Cerebras-GPT, GPT-2, GPT-Neo, and GPT-J architectures. The maintainer MBZUAI recommends using the models with the best overall performance given their size/architecture. Model inputs and outputs Inputs Natural language instructions**: The model is designed to respond to human instructions written in natural language. Outputs Generated text**: The model generates a response text based on the provided instruction. Capabilities The LaMini-Flan-T5-783M model is capable of understanding and executing a wide range of natural language instructions, such as question answering, text summarization, and language translation. Its fine-tuning on the LaMini-instruction dataset has further enhanced its ability to handle diverse tasks. What can I use it for? You can use the LaMini-Flan-T5-783M model for research on language models, including zero-shot and few-shot learning tasks, as well as exploring fairness and safety aspects of large language models. The model can also be used as a starting point for fine-tuning on specific applications, as its instruction-based training has improved its performance and usability compared to the original Flan-T5 model. Things to try One interesting aspect of the LaMini-Flan-T5-783M model is its ability to handle instructions in multiple languages, as it has been trained on a diverse dataset covering over 50 languages. You could experiment with providing instructions in different languages and observe the model's performance. Additionally, you could try prompting the model with open-ended instructions to see the breadth of tasks it can handle and the quality of its responses.
Updated 5/28/2024
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LaMini-Flan-T5-248M
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The LaMini-Flan-T5-248M model is part of the LaMini-LM series developed by MBZUAI. It is a fine-tuned version of the google/flan-t5-base model, further trained on the LaMini-instruction dataset containing 2.58M samples. This series includes several other models like LaMini-Flan-T5-77M, LaMini-Flan-T5-783M, and more, providing a range of model sizes to choose from. The models are designed to perform well on a variety of instruction-based tasks. Model inputs and outputs Inputs Text prompts in natural language that describe a task or instruction for the model to perform Outputs Text responses generated by the model to complete the given task or instruction Capabilities The LaMini-Flan-T5-248M model is capable of understanding and responding to a wide range of natural language instructions, from simple translations to more complex problem-solving tasks. It demonstrates strong performance on benchmarks covering reasoning, question-answering, and other instruction-based challenges. What can I use it for? The LaMini-Flan-T5-248M model can be used for research on language models, including exploring zero-shot and few-shot learning on NLP tasks. It may also be useful for applications that require natural language interaction, such as virtual assistants, content generation, and task automation. However, as with any large language model, care should be taken to assess potential safety and fairness concerns before deploying it in real-world applications. Things to try Experiment with the model's few-shot capabilities by providing it with minimal instructions and observing its responses. You can also try fine-tuning the model on domain-specific datasets to see how it adapts to specialized tasks. Additionally, exploring the model's multilingual capabilities by testing it on prompts in different languages could yield interesting insights.
Updated 5/28/2024
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LaMini-T5-738M
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The LaMini-T5-738M is one of the models in the LaMini-LM series developed by MBZUAI. It is a fine-tuned version of the t5-large model that has been further trained on the LaMini-instruction dataset, which contains 2.58M samples for instruction fine-tuning. The LaMini-LM series includes several models with different parameter sizes, ranging from 61M to 1.3B, allowing users to choose the one that best fits their needs. The maintainer, MBZUAI, provides a profile page with more information about their work. Model inputs and outputs The LaMini-T5-738M model is a text-to-text generation model, meaning it takes in natural language prompts as input and generates relevant text as output. The model can be used to respond to human instructions written in natural language. Inputs Natural language prompts**: The model accepts natural language prompts as input, such as "Please let me know your thoughts on the given place and why you think it deserves to be visited: 'Barcelona, Spain'". Outputs Generated text**: The model generates relevant text in response to the input prompt. The output can be up to 512 tokens long. Capabilities The LaMini-T5-738M model has been trained on a diverse set of instructions, allowing it to perform a wide range of natural language processing tasks such as question answering, task completion, and text generation. The model has demonstrated strong performance on various benchmarks, outperforming larger models like Llama2-13B, MPT-30B, and Falcon-40B in certain areas. What can I use it for? The LaMini-T5-738M model can be used for a variety of applications that involve responding to human instructions written in natural language. This could include customer service chatbots, virtual assistants, content generation, and task automation. The model's performance and relatively small size make it a suitable choice for deployment on edge devices or in resource-constrained environments. Things to try One interesting aspect of the LaMini-T5-738M model is its ability to handle diverse instructions and generate coherent and relevant responses. Users could experiment with prompts that cover a wide range of topics, from open-ended questions to specific task descriptions, to see the model's flexibility and capabilities. Additionally, users could compare the performance of the LaMini-T5-738M model to other models in the LaMini-LM series to determine the optimal trade-off between model size and performance for their specific use case.
Updated 9/6/2024