Llama 3.1 70B Instruct
Transform multilingual dialogues with this advanced language model.
A model designed for natural language tasks, Meta-Llama-3.1-70B-Instruct has impressive benchmark scores. Fine-tuning for instructions enhances its versatility. It's ideal for developers looking for robust multilingual capabilities.
License | llama3.1 |
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Context window(in thousands) | 131072 |
Use cases for Llama 3.1 70B Instruct
- Large-scale document parsing: Useful for extracting and summarizing information from large documents or databases.
- Chatbots and virtual assistants: Enhances interaction quality in customer service chatbots and virtual assistants.
- Language translation: Can be applied in real-time language translation systems to improve accuracy.
Arena Elo | 1248 |
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MMLU | N/A |
MT Bench | N/A |
The LLM Leaderboard shows Llama 3.1 70B Instruct with a score of 1242, higher than Llama 3 Instruct 70B at 1206.
1316
1251
1248
1245
1206
Throughput(output tokens per second) | N/A |
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Latency(seconds to first tokens chunk received) | N/A |
Total Response Time(seconds to output 100 tokens) | N/A |
What's Twitter saying?
- Performance comparison: Zhijiang Guo discusses the performance of Llama 3.1 70B compared to Llama 3 70B in function-level code generation, as evidenced by Humaneval and MHPP results. @ZhijiangG
- Uncensored model release: Maxime Labonne announces the launch of an uncensored version of Llama 3.1 70B Instruct, utilizing grimjim's LoRA + abliteration recipe. The model is noted for its high quality despite being uncensored. @maximelabonne
- Technical summary of new release: Gradio provides an in-depth, bullet-point summary of Meta's Llama 3.1 release, covering sizes, new licensing terms, multilingual support, and efficiency improvements. @Gradio
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What is the Meta Llama 3.1 70B Instruct model?
The Meta Llama 3.1 70B Instruct is a state-of-the-art large language model developed by Meta AI. It supports eight languages, uses an optimized transformer architecture, and is designed for dialogue use cases with a focus on multilingual support, safety, and performance.
How does Llama 3.1 70B Instruct compare to GPT models?
The Llama 3.1 70B Instruct model is designed to be more versatile and multilingual than GPT models like GPT-4 and Claude 3.5 Sonnet. It offers superior performance across common industry benchmarks, a longer context window, and enhanced safety features.
What languages does Llama 3.1 70B support?
It supports eight languages: English, French, German, Hindi, Italian, Portuguese, Spanish, and Thai, making it suitable for a wide range of global applications source.
What are the main features of the Meta Llama 3.1 70B Instruct model?
Key features include multilingual support, an optimized transformer architecture, a context length of 128K, training on over 15 trillion tokens, and advanced safety measures like Llama Guard 3, Prompt Guard, and Code Shield.
How can I use the Llama 3.1 70B Instruct model in my projects?
Developers can integrate the Llama 3.1 70B Instruct model into their projects, including connectivity apps, by using platforms like Telnyx. For more information on getting started, visit Telnyx's developer documentation.
What safety measures are in place for the Llama 3.1 70B Instruct model?
Meta AI has implemented several safety and security measures, including Llama Guard 3, Prompt Guard, and Code Shield, to ensure the model's responsible use and deployment in various applications.
How does Llama 3.1 70B Instruct perform on industry benchmarks?
The Llama 3.1 70B Instruct model outperforms many open source and closed chat models on common industry benchmarks, making it one of the most capable models available for developers and researchers source.
Where can I find more information about integrating Llama 3.1 70B Instruct with my app?
To learn more about integrating the Llama 3.1 70B Instruct model into your app, especially for connectivity purposes, you can visit Telnyx's developer documentation.