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Llama 3 70B Instruct Gradient 524K by gradientai

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Llama 3 70B Instruct Gradient 524K is an open-source language model by gradientai. Features: 70b LLM, VRAM: 141.9GB, Context: 512K, License: llama3, Instruction-Based, HF Score: 74, LLM Explorer Score: 0.14, Arc: 66.8, HellaSwag: 85.5, MMLU: 76.4, TruthfulQA: 53.7, WinoGrande: 82.6, GSM8K: 78.9.

  Arxiv:2305.14233   Arxiv:2309.00071   Arxiv:2310.05209   Arxiv:2402.08268   Conversational   Doi:10.57967/hf/3370   En   Endpoints compatible   Instruct   Llama   Llama-3   Meta   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/gradientai/Llama-3-70B-Instruct-Gradient-524k 

Llama 3 70B Instruct Gradient 524K Benchmarks

ARC: 66.81 vs 96.7 (so35)-30.9%
HellaSwag: 85.46 vs 95.3 (gpt4)-10.3%
MMLU: 76.37 vs 88.3 (so35)-13.5%
TruthfulQA: 53.73 vs 59 (gpt4)-8.9%
WinoGrande: 82.64 vs 87.5 (gpt4)-5.6%
GSM8K: 78.85 vs 96.4 (so35)-18.2%
LLME Score: 0.14465
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 70B Instruct Gradient 524K (gradientai/Llama-3-70B-Instruct-Gradient-524k)
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Llama 3 70B Instruct Gradient 524K Parameters and Internals

Model Type 
text-generation, instruction-tuned
Use Cases 
Areas:
commercial, research
Primary Use Cases:
assistant-like chat, natural language generation tasks
Limitations:
Use limited to English, Potential for unpredictable outputs
Considerations:
Developers should exercise discretion.
Supported Languages 
English (full support)
Training Details 
Data Sources:
SlimPajama, UltraChat
Data Volume:
<0.003% of Llama-3's original pre-training data
Methodology:
NTK-aware interpolation, Progressive training
Context Length:
524000
Hardware Used:
NVIDIA L40S
Model Architecture:
Auto-regressive transformer
Safety Evaluation 
Methodologies:
red teaming exercises, adversarial evaluations
Risk Categories:
CBRNE, Cyber Security, Child Safety
Responsible Ai Considerations 
Transparency:
Responsible Use Guide available.
Accountability:
Developers are responsible for application deployment.
Mitigation Strategies:
Safety best practices, Purple Llama tools, Llama Guard
Input Output 
Input Format:
text
Accepted Modalities:
text
Output Format:
text, code
Release Notes 
Version:
0
Date:
2024-04-18
Notes:
Model release. Static model.
LLM NameLlama 3 70B Instruct Gradient 524K
Repository 🤗https://huggingface.co/gradientai/Llama-3-70B-Instruct-Gradient-524k 
Model Size70b
Required VRAM141.9 GB
Updated2026-04-16
Maintainergradientai
Model Typellama
Instruction-BasedYes
Model Files  4.6 GB: 1-of-30   4.7 GB: 2-of-30   5.0 GB: 3-of-30   5.0 GB: 4-of-30   4.7 GB: 5-of-30   4.7 GB: 6-of-30   4.7 GB: 7-of-30   5.0 GB: 8-of-30   5.0 GB: 9-of-30   4.7 GB: 10-of-30   4.7 GB: 11-of-30   4.7 GB: 12-of-30   5.0 GB: 13-of-30   5.0 GB: 14-of-30   4.7 GB: 15-of-30   4.7 GB: 16-of-30   4.7 GB: 17-of-30   5.0 GB: 18-of-30   5.0 GB: 19-of-30   4.7 GB: 20-of-30   4.7 GB: 21-of-30   4.7 GB: 22-of-30   5.0 GB: 23-of-30   5.0 GB: 24-of-30   4.7 GB: 25-of-30   4.7 GB: 26-of-30   4.7 GB: 27-of-30   5.0 GB: 28-of-30   5.0 GB: 29-of-30   2.1 GB: 30-of-30
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length524288
Model Max Length524288
Transformers Version4.41.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

Quantized Models of the Llama 3 70B Instruct Gradient 524K

Model
Likes
Downloads
VRAM
...70B Instruct Gradient 262K AWQ0639 GB
...0B Instruct Gradient 262K 4bit33239 GB
...0B Instruct Gradient 262K 8bit21575 GB
...0B Instruct Gradient 262K 2bit1921 GB

Best Alternatives to Llama 3 70B Instruct Gradient 524K

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...ama 3 70B Arimas Story RP V1.6256K / 141.2 GB130
...ama 3 70B Arimas Story RP V1.5256K / 141.2 GB83
Llama 3.1 70B Instruct128K / 141.9 GB1008029904
...a 3.1 Nemotron 70B Instruct HF128K / 141.9 GB114102063
Note: green Score (e.g. "73.2") means that the model is better than gradientai/Llama-3-70B-Instruct-Gradient-524k.

Rank the Llama 3 70B Instruct Gradient 524K Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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