Meta-Llama-3-8B
Maintainer: meta-llama
2.7K
🎯
Property | Value |
---|---|
Run this model | Run on HuggingFace |
API spec | View on HuggingFace |
Github link | No Github link provided |
Paper link | No paper link provided |
Create account to get full access
Model overview
The Meta-Llama-3-8B
is an 8-billion parameter language model developed and released by Meta. It is part of the Llama 3 family of large language models (LLMs), which also includes a 70-billion parameter version. The Llama 3 models are optimized for dialogue use cases and outperform many open-source chat models on common benchmarks. The instruction-tuned version is particularly well-suited for assistant-like applications.
The Llama 3 models use an optimized transformer architecture and were trained on over 15 trillion tokens of data from publicly available sources. The 8B and 70B models both use Grouped-Query Attention (GQA) for improved inference scalability. The instruction-tuned versions leveraged supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align the models with human preferences for helpfulness and safety.
Model inputs and outputs
Inputs
- Text input only
Outputs
- Generates text and code
Capabilities
The Meta-Llama-3-8B
model excels at a variety of natural language generation tasks, including open-ended conversations, question answering, and code generation. It outperforms previous Llama models and many other open-source LLMs on standard benchmarks, with particularly strong performance on tasks that require reasoning, commonsense understanding, and following instructions.
What can I use it for?
The Meta-Llama-3-8B
model is well-suited for a range of commercial and research applications that involve natural language processing and generation. The instruction-tuned version can be used to build conversational AI assistants for customer service, task automation, and other applications where helpful and safe language models are needed. The pre-trained model can also be fine-tuned for specialized tasks like content creation, summarization, and knowledge distillation.
Things to try
Try using the Meta-Llama-3-8B
model in open-ended conversations to see its capabilities in areas like task planning, creative writing, and answering follow-up questions. The model's strong performance on commonsense reasoning benchmarks suggests it could be useful for applications that require understanding the real-world context. Additionally, the model's ability to generate code makes it a potentially valuable tool for developers looking to leverage language models for programming assistance.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
Related Models
🌿
Meta-Llama-3-70B
506
The meta-llama/Meta-Llama-3-70B is a large language model (LLM) developed and released by Meta. It is part of the Llama 3 family of models, which includes both 8B and 70B parameter versions in both pre-trained and instruction-tuned variants. The Llama 3 instruction-tuned models are optimized for dialogue use cases and outperform many available open-source chat models on common industry benchmarks. Meta has taken great care to optimize the helpfulness and safety of these models. Similar models include the Meta-Llama-3-70B-Instruct and the Meta-Llama-3-8B-Instruct, which are part of the same Llama 3 model family. Model inputs and outputs Inputs Text**: The Meta-Llama-3-70B model takes text as input. Outputs Text and code**: The model generates text and code as output. Capabilities The Meta-Llama-3-70B model is a powerful generative language model capable of a wide range of natural language processing tasks. It has demonstrated strong performance on benchmarks covering commonsense reasoning, world knowledge, reading comprehension, and more. The instruction-tuned versions of the model are particularly adept at assistant-like chat, outperforming many open-source chat models. What can I use it for? The Meta-Llama-3-70B model can be used for a variety of commercial and research applications that involve natural language generation, such as chatbots, content creation, and code generation. The pre-trained version can be further fine-tuned for specific use cases, while the instruction-tuned models are well-suited for interactive assistant applications. Things to try One interesting aspect of the Meta-Llama-3-70B model is its emphasis on safety and helpfulness. Meta has put a lot of work into mitigating risks and ensuring the model provides useful and truthful responses, even to potentially harmful prompts. Developers should explore ways to leverage the model's safety features and continue to test its performance in their specific use cases.
Updated Invalid Date
🎯
Meta-Llama-3-8B
76
The Meta-Llama-3-8B is part of the Meta Llama 3 family of large language models (LLMs) developed and released by Meta. This collection of pretrained and instruction tuned generative text models comes in 8B and 70B parameter sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many available open source chat models on common industry benchmarks. Meta took great care to optimize helpfulness and safety when developing these models. The Meta-Llama-3-70B and Meta-Llama-3-8B-Instruct are other models in the Llama 3 family. The 70B parameter model provides higher performance than the 8B, while the 8B Instruct model is optimized for assistant-like chat. Model inputs and outputs Inputs The Meta-Llama-3-8B model takes text input only. Outputs The model generates text and code output. Capabilities The Meta-Llama-3-8B demonstrates strong performance on a variety of natural language processing benchmarks, including general knowledge, reading comprehension, and task-oriented dialogue. It excels at following instructions and engaging in open-ended conversations. What can I use it for? The Meta-Llama-3-8B is intended for commercial and research use in English. The instruction tuned version is well-suited for building assistant-like chat applications, while the pretrained model can be adapted for a range of natural language generation tasks. Developers can leverage the Llama Guard and other Purple Llama tools to enhance the safety and reliability of applications using this model. Things to try The clear strength of the Meta-Llama-3-8B model is its ability to engage in open-ended, task-oriented dialogue. Developers can leverage this by building conversational interfaces that leverage the model's instruction-following capabilities to complete a wide variety of tasks. Additionally, the model's strong grounding in general knowledge makes it well-suited for building information lookup tools and knowledge bases.
Updated Invalid Date
✅
Meta-Llama-3-8B-GGUF
48
The Meta-Llama-3-8B-GGUF is part of the Meta Llama 3 family of large language models (LLMs) developed by NousResearch. This 8 billion parameter model is available in both pretrained and instruction-tuned variants, with the instruction-tuned version optimized for dialogue use cases. Compared to the Meta-Llama-3-8B and Meta-Llama-3-70B models, the Meta-Llama-3-8B-GGUF has been further tuned for helpfulness and safety. Model inputs and outputs Inputs The Meta-Llama-3-8B-GGUF model takes in text as input. Outputs The model generates text and code as output. Capabilities The Meta-Llama-3-8B-GGUF model demonstrates strong performance on a variety of natural language tasks, including general language understanding, knowledge reasoning, and reading comprehension. It outperforms many open-source chat models on common industry benchmarks. The instruction-tuned version is particularly well-suited for assistant-like conversational interactions. What can I use it for? The Meta-Llama-3-8B-GGUF model is intended for commercial and research use in English, with the instruction-tuned version targeted at assistant-like chat applications. Developers can also adapt the pretrained version for a range of natural language generation tasks. As with any large language model, it's important to consider potential risks and implement appropriate safeguards when deploying the model. Things to try One interesting aspect of the Meta-Llama-3-8B-GGUF model is its emphasis on helpfulness and safety. Developers should explore the Responsible Use Guide and tools like Meta Llama Guard and Code Shield to ensure their applications leverage the model's capabilities while mitigating potential risks.
Updated Invalid Date
🛠️
Meta-Llama-3-8B-Instruct
1.5K
The Meta-Llama-3-8B-Instruct is a large language model developed and released by Meta. It is part of the Llama 3 family of models, which come in 8 billion and 70 billion parameter sizes, with both pretrained and instruction-tuned variants. The instruction-tuned Llama 3 models are optimized for dialogue use cases and outperform many open-source chat models on common industry benchmarks. Meta has taken care to optimize these models for helpfulness and safety. The Llama 3 models use an optimized transformer architecture and were trained on a mix of publicly available online data. The 8 billion parameter version uses a context length of 8k tokens and is capable of tasks like commonsense reasoning, world knowledge, reading comprehension, and math. Compared to the earlier Llama 2 models, the Llama 3 models have improved performance across a range of benchmarks. Model inputs and outputs Inputs Text input only Outputs Generates text and code Capabilities The Meta-Llama-3-8B-Instruct model is capable of a variety of natural language generation tasks, including dialogue, summarization, question answering, and code generation. It has shown strong performance on benchmarks evaluating commonsense reasoning, world knowledge, reading comprehension, and math. What can I use it for? The Meta-Llama-3-8B-Instruct model is intended for commercial and research use in English. The instruction-tuned variants are well-suited for assistant-like chat applications, while the pretrained models can be further fine-tuned for a range of text generation tasks. Developers should carefully review the Responsible Use Guide before deploying the model in production. Things to try Developers may want to experiment with fine-tuning the Meta-Llama-3-8B-Instruct model on domain-specific data to adapt it for specialized applications. The model's strong performance on benchmarks like commonsense reasoning and world knowledge also suggests it could be a valuable foundation for building knowledge-intensive applications.
Updated Invalid Date