
Llama3 Gradient 8B Instruct

Llama3 Gradient 8B Instruct is a large language model developed by Meta Llama, a company, with 8B parameters. It operates under the Meta Llama 3 Community License Agreement (META-LLAMA-3-CCLA) and is designed for instruct tasks. The model excels in handling extended context lengths, supporting up to 1 million tokens, making it suitable for complex and lengthy interactions.
Description of Llama3 Gradient 8B Instruct
Meta Llama 3 is a family of large language models (LLMs) developed by Meta, available in 8B and 70B parameter sizes. It includes pretrained and instruction-tuned variants optimized for dialogue use cases, with enhanced safety and helpfulness features. The models are trained on diverse data and designed for commercial, research, and application-specific tasks.
Parameters & Context Length of Llama3 Gradient 8B Instruct
The Llama3 Gradient 8B Instruct model features 8b parameters, placing it in the mid-scale category, offering balanced performance for moderate complexity tasks. Its 8k context length supports moderate-length interactions, making it suitable for extended tasks while remaining resource-efficient. This configuration ensures efficiency for applications requiring moderate computational resources and text length.
- Name: Llama3 Gradient 8B Instruct
- Parameter_Size: 8b
- Context_Length: 8k
- Implications: Mid-scale parameters for balanced performance, 8k context for moderate-length tasks.
Possible Intended Uses of Llama3 Gradient 8B Instruct
The Llama3 Gradient 8B Instruct model offers possible applications in assistant-like chat scenarios, where its design could support conversational interactions with users. It may also serve as a possible tool for research tasks, providing insights or generating text for exploratory work. Additionally, it could be used for natural language generation tasks, such as creating content or analyzing text patterns. These possible uses require thorough evaluation to ensure alignment with specific goals and constraints. The model’s parameters and context length suggest it is suited for tasks that balance efficiency and capability, but further investigation is needed to confirm its effectiveness in these areas.
- Intended_Uses: assistant-like chat
- Intended_Uses: research
- Intended_Uses: natural language generation tasks
Possible Applications of Llama3 Gradient 8B Instruct
The Llama3 Gradient 8B Instruct model presents possible applications in assistant-like chat scenarios, where its design could support interactive dialogue with users. It may also offer possible value in research settings, aiding in exploratory tasks or data analysis. Additionally, it could be used for natural language generation tasks, such as drafting text or generating creative content. Possible uses in content creation or data processing might also align with its capabilities. These possible applications require careful assessment to ensure they meet specific requirements and constraints. Each application must be thoroughly evaluated and tested before deployment.
- Name: Llama3 Gradient 8B Instruct
- Possible Applications: assistant-like chat
- Possible Applications: research
- Possible Applications: natural language generation tasks
- Possible Applications: content creation
Quantized Versions & Hardware Requirements of Llama3 Gradient 8B Instruct
The Llama3 Gradient 8B Instruct model with q4 quantization requires a GPU with at least 16GB VRAM and system memory of at least 32GB for optimal performance, making it suitable for mid-range hardware setups. This possible configuration balances precision and efficiency, allowing the model to run on devices with moderate computational resources. However, specific requirements may vary based on workload and implementation.
- Quantized_Versions: fp16, q2, q3, q4, q5, q6, q8
Conclusion
Llama3 Gradient 8B Instruct is a large language model with 8B parameters and a 8k context length, developed by Meta Llama. It is designed for instruct tasks, offering a balance between performance and resource efficiency for moderate-scale applications.
References
Benchmarks
Benchmark Name | Score |
---|---|
Instruction Following Evaluation (IFEval) | 14.55 |
Big Bench Hard (BBH) | 24.50 |
Mathematical Reasoning Test (MATH Lvl 5) | 4.53 |
General Purpose Question Answering (GPQA) | 7.38 |
Multimodal Understanding and Reasoning (MUSR) | 6.24 |
Massive Multitask Language Understanding (MMLU-PRO) | 24.55 |
