Maziyarpanahi
Models by this creator
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Meta-Llama-3-70B-Instruct-GGUF
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Meta-Llama-3-70B-Instruct-GGUF is a large language model developed by Meta that is part of the Llama 3 family of models. It is a 70 billion parameter model that has been instruction tuned, meaning it has been optimized for dialogue and assistant-like use cases. Compared to the base Meta-Llama-3-70B-Instruct model, this version has been quantized using the Grouped-Query Attention (GQA) technique, which allows it to have lower memory usage and faster inference speeds. The model was created by MaziyarPanahi and is available on the Hugging Face Hub. The Llama 3 models represent a significant advancement over the previous Llama 2 models, with the 70B parameter version matching or exceeding the performance of GPT-3.5 on a variety of benchmarks. This is an impressive accomplishment, as Llama 3 is an open model that outperforms a much larger closed model. The instruction tuning process used for Llama 3 has also resulted in a model that is highly capable at following instructions and engaging in helpful dialogues. Model inputs and outputs Inputs The model takes in text inputs only. Outputs The model generates natural language text as output. It can also generate code snippets when prompted. Capabilities The Meta-Llama-3-70B-Instruct-GGUF model is a powerful language model that excels at a wide variety of natural language tasks. It has demonstrated strong performance on benchmarks evaluating general knowledge, reading comprehension, and common sense reasoning. The model is also highly capable at engaging in open-ended dialogue and following instructions, making it well-suited for assistant-like use cases. What can I use it for? The Meta-Llama-3-70B-Instruct-GGUF model can be used for a variety of natural language processing tasks, such as: Dialogue and conversational AI**: The model's instruction tuning and strong performance on benchmarks make it well-suited for building helpful, engaging chatbots and virtual assistants. Content generation**: The model can be used to generate high-quality text on a wide range of topics, from creative writing to technical documentation. Code generation**: The model has shown the ability to generate functional code snippets when prompted, making it useful for tools and applications that require code generation capabilities. Things to try One interesting aspect of Meta-Llama-3-70B-Instruct-GGUF is its strong performance on benchmarks evaluating reasoning and common sense, which suggests it may be well-suited for tasks that require deeper understanding of the world. Developers could experiment with prompting the model to engage in more complex reasoning or problem-solving tasks, and see how it performs. Another interesting area to explore would be the model's capabilities around safety and responsible AI. Meta has put a strong emphasis on responsible development and release of the Llama 3 models, and has provided resources like the Responsible Use Guide to help developers deploy the models safely. Developers could look into leveraging these resources and tools to build applications that leverage the model's capabilities while mitigating potential risks.
Updated 5/28/2024
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WizardLM-2-8x22B-GGUF
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The MaziyarPanahi/WizardLM-2-8x22B-GGUF model is based on the original microsoft/WizardLM-2-8x22B model. It is a variant of the WizardLM-2 family of large language models developed by Microsoft, with files in the GGUF format for use with tools like llama.cpp. Similar models in this family include the MaziyarPanahi/WizardLM-2-7B-GGUF which has a smaller 7B parameter size. Model inputs and outputs The WizardLM-2-8x22B-GGUF model is a text-to-text model, taking in natural language prompts as input and generating relevant text responses as output. It can handle a wide range of tasks like answering questions, generating stories, and providing task-oriented assistance. Inputs Natural language prompts**: The model accepts free-form text prompts describing a task or request. Outputs Generated text**: The model outputs relevant text responses to complete the requested task or answer the given prompt. Capabilities The WizardLM-2-8x22B-GGUF model demonstrates strong performance across a variety of language understanding and generation benchmarks. It outperforms many leading open-source models in areas like complex chat, reasoning, and multilingual capabilities. The model can handle tasks like question answering, task-oriented dialogue, and open-ended text generation with a high degree of fluency and coherence. What can I use it for? The WizardLM-2-8x22B-GGUF model can be used for a wide range of natural language processing applications, such as: Chatbots and virtual assistants**: The model can be used to build conversational AI agents that can engage in helpful and engaging dialogues. Content generation**: The model can be used to generate high-quality text content like articles, stories, and product descriptions. Question answering**: The model can be used to build systems that can answer a wide range of questions accurately and informatively. Task-oriented assistance**: The model can be used to build AI assistants that can help users complete specific tasks like writing, coding, or math problems. Things to try Some interesting things to try with the WizardLM-2-8x22B-GGUF model include: Exploring the model's multilingual capabilities by prompting it in different languages. Evaluating the model's reasoning and problem-solving skills on complex tasks like mathematical word problems or coding challenges. Experimenting with different prompt engineering techniques to see how the model's responses can be tailored for specific use cases. Comparing the performance of this model to similar large language models like WizardLM-2-7B-GGUF or GPT-based models. Overall, the WizardLM-2-8x22B-GGUF model represents a powerful and versatile text generation system that can be applied to a wide range of natural language processing tasks.
Updated 5/28/2024
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Meta-Llama-3-8B-Instruct-GGUF
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Meta-Llama-3-8B-Instruct-GGUF is a large language model developed by MaziyarPanahi that is part of the Meta Llama 3 family of models. This 8B parameter model is an instruction-tuned version, optimized for dialogue and assistant tasks. It outperforms many open-source chat models on industry benchmarks, while also being optimized for safety and helpfulness. The model is based on the original Meta-Llama-3-8B-Instruct model, with additional GGUF (Grouped-Query Attention) quantization for improved efficiency. Model inputs and outputs Inputs Text inputs only Outputs Generates text and code Capabilities Meta-Llama-3-8B-Instruct-GGUF excels at a variety of natural language tasks, including multi-turn conversations, general knowledge, and coding. It can engage in creative conversations, answer trivia questions, and provide code solutions. The model's instruction-tuning allows it to follow prompts and guidelines effectively, making it a capable AI assistant. What can I use it for? This model can be used for a wide range of applications that require natural language understanding and generation, such as chatbots, virtual assistants, content creation, and code generation. Developers can fine-tune the model further for specific use cases or deploy it as-is for general-purpose assistance. The Meta-Llama-3-70B-Instruct-GGUF model provides an even larger and more capable version for more demanding applications. Things to try Try engaging the model in open-ended conversations to see its dialogue capabilities, or provide it with coding challenges or trivia questions to test its knowledge and problem-solving skills. You can also experiment with different system prompts to customize the model's behavior, such as making it a pirate chatbot or a scientific advisor. The model's instruction-following abilities make it a versatile tool for a variety of use cases.
Updated 5/28/2024
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Mixtral-8x22B-v0.1-GGUF
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The Mixtral-8x22B-v0.1-GGUF is a large language model with 176B parameters, created by MistralAI. It is a sparse mixture of experts model that outperforms the 70B Llama 2 model on many benchmarks. The model is available in quantized GGUF format, which allows for efficient CPU and GPU inference. Model inputs and outputs Inputs Raw text prompts of varying lengths, up to 65,000 tokens Outputs Continuation of the input text, generating coherent and contextual responses The model can be used for a variety of text generation tasks, such as story writing, question answering, and open-ended conversation Capabilities The Mixtral-8x22B-v0.1-GGUF model demonstrates strong performance on a range of benchmarks, including the AI2 Reasoning Challenge, HellaSwag, MMLU, TruthfulQA, Winogrande, and GSM8k. It is capable of generating human-like text across diverse domains and tasks. What can I use it for? The Mixtral-8x22B-v0.1-GGUF model can be used for a variety of natural language processing tasks, such as content generation, chatbots, and language modeling. Its large size and strong performance make it well-suited for applications that require sophisticated language understanding and generation, such as creative writing assistants, question-answering systems, and virtual assistants. Things to try Experiment with the model's ability to maintain coherence and context over long sequences of text. Try providing it with open-ended prompts and observe how it builds upon and develops the narrative. Additionally, you can fine-tune the model on specialized datasets to adapt it to specific domains or tasks, unlocking even more capabilities.
Updated 5/27/2024
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WizardLM-2-7B-GGUF
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MaziyarPanahi/WizardLM-2-7B-GGUF is an AI model developed by MaziyarPanahi that contains GGUF format model files for the microsoft/WizardLM-2-7B model. This model is part of the WizardLM family, which includes cutting-edge large language models like WizardLM-2 8x22B, WizardLM-2 70B, and WizardLM-2 7B. These models demonstrate strong performance on tasks like complex chat, multilingual capabilities, reasoning, and agent abilities. Model inputs and outputs Inputs Text prompts Outputs Continued text generation Capabilities The WizardLM-2-7B-GGUF model can be used for a variety of natural language processing tasks, including open-ended text generation, language modeling, and dialogue systems. It has shown strong performance on benchmarks like HumanEval, MBPP, and GSM8K. What can I use it for? You can use the WizardLM-2-7B-GGUF model for projects that require advanced language understanding and generation capabilities, such as chatbots, content creation tools, code generation assistants, and more. The model's strong performance on reasoning and multi-lingual tasks also make it suitable for applications that require those capabilities. Things to try Try using the WizardLM-2-7B-GGUF model to generate creative stories, engage in open-ended conversations, or assist with coding tasks. Experiment with different prompting techniques and see how the model responds. You can also fine-tune the model on your own data to adapt it to your specific use case.
Updated 5/28/2024
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Mistral-7B-Instruct-v0.3-GGUF
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The Mistral-7B-Instruct-v0.3-GGUF model is a text-to-text AI model created by Mistral AI. It is an instruction-tuned version of the Mistral-7B-v0.1 model, which outperforms the Llama 2 13B model on various benchmarks. The model uses grouped-query attention, sliding-window attention, and a byte-fallback BPE tokenizer in its architecture. Similar models include the Llama-3-8B-Instruct-32k-v0.1-GGUF and the Mistral-7B-Instruct-v0.1-GGUF, both of which are also instruction-tuned large language models. Model inputs and outputs Inputs Text prompts that can be used to instruct the model to perform various tasks, such as answering questions, generating text, or completing tasks. Outputs Generated text outputs that respond to the provided prompts, following the given instructions. Capabilities The Mistral-7B-Instruct-v0.3-GGUF model is capable of generating coherent and contextually appropriate text in response to a wide range of prompts. It can be used for tasks such as question answering, text summarization, creative writing, and task completion. The model has been fine-tuned on instructional datasets to improve its ability to follow instructions and complete tasks. What can I use it for? The Mistral-7B-Instruct-v0.3-GGUF model can be used for a variety of applications, such as developing virtual assistants, chatbots, or content generation tools. It could be used by companies to automate customer service tasks, generate marketing copy, or create personalized content for their customers. Researchers and developers could also use the model as a starting point for fine-tuning or further development of language models for their specific needs. Things to try One interesting thing to try with the Mistral-7B-Instruct-v0.3-GGUF model is to provide it with multi-step instructions or tasks, and see how well it is able to follow and complete them. You could also experiment with different prompting techniques, such as using targeted questions or providing additional context, to see how the model's outputs change.
Updated 8/7/2024
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Llama-3-8B-Instruct-32k-v0.1-GGUF
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The Llama-3-8B-Instruct-32k-v0.1-GGUF is a large language model created by MaziyarPanahi. It is based on the original MaziyarPanahi/Llama-3-8B-Instruct-32k-v0.1 model and is available in the GGUF format. The GGUF format is a new format introduced by the llama.cpp team and is a replacement for the GGML format. Model inputs and outputs The Llama-3-8B-Instruct-32k-v0.1-GGUF model is a text-to-text AI model, meaning it takes text as input and generates text as output. Inputs Text prompts Outputs Generated text based on the input prompt Capabilities The Llama-3-8B-Instruct-32k-v0.1-GGUF model is capable of a wide range of text generation tasks, such as summarization, translation, and question answering. It can be used to generate coherent and contextually relevant text on a variety of topics. What can I use it for? The Llama-3-8B-Instruct-32k-v0.1-GGUF model can be used in a variety of applications, such as chatbots, content generation, and language understanding. It can also be fine-tuned on specific tasks or datasets to improve its performance on those tasks. Things to try Some ideas for things to try with the Llama-3-8B-Instruct-32k-v0.1-GGUF model include generating creative stories, answering questions on a wide range of topics, and exploring the model's capabilities through various prompts and tasks.
Updated 6/13/2024
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Llama-3-8B-Instruct-32k-v0.1-GGUF
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The Llama-3-8B-Instruct-32k-v0.1-GGUF is a large language model created by MaziyarPanahi. It is based on the original MaziyarPanahi/Llama-3-8B-Instruct-32k-v0.1 model and is available in the GGUF format. The GGUF format is a new format introduced by the llama.cpp team and is a replacement for the GGML format. Model inputs and outputs The Llama-3-8B-Instruct-32k-v0.1-GGUF model is a text-to-text AI model, meaning it takes text as input and generates text as output. Inputs Text prompts Outputs Generated text based on the input prompt Capabilities The Llama-3-8B-Instruct-32k-v0.1-GGUF model is capable of a wide range of text generation tasks, such as summarization, translation, and question answering. It can be used to generate coherent and contextually relevant text on a variety of topics. What can I use it for? The Llama-3-8B-Instruct-32k-v0.1-GGUF model can be used in a variety of applications, such as chatbots, content generation, and language understanding. It can also be fine-tuned on specific tasks or datasets to improve its performance on those tasks. Things to try Some ideas for things to try with the Llama-3-8B-Instruct-32k-v0.1-GGUF model include generating creative stories, answering questions on a wide range of topics, and exploring the model's capabilities through various prompts and tasks.
Updated 6/13/2024