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Gradientai Llama 3 8B Instruct 262K V2 EXL2 8.0bpw by bullerwins

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Gradientai Llama 3 8B Instruct 262K V2 EXL2 8.0bpw is an open-source language model by bullerwins. Features: 8b LLM, VRAM: 8.4GB, Context: 256K, License: llama3, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

  Arxiv:2305.14233   Arxiv:2309.00071   Arxiv:2402.08268   8-bit   Conversational   En   Endpoints compatible   Exl2   Instruct   Llama   Llama-3   Meta   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/bullerwins/gradientai_Llama-3-8B-Instruct-262k_v2_exl2_8.0bpw 

Gradientai Llama 3 8B Instruct 262k V2 EXL2 8.0bpw Benchmarks

LLME Score: 0.1316
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Gradientai Llama 3 8B Instruct 262K V2 EXL2 8.0bpw (bullerwins/gradientai_Llama-3-8B-Instruct-262k_v2_exl2_8.0bpw)
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Gradientai Llama 3 8B Instruct 262K V2 EXL2 8.0bpw Parameters and Internals

Model Type 
text generation, instruction-tuned
Use Cases 
Areas:
commercial, research
Applications:
assistant-like chat
Primary Use Cases:
natural language generation tasks
Limitations:
English only; out-of-scope for illegal or prohibited use cases
Considerations:
Developers may fine-tune for languages beyond English adhering to specific policies.
Additional Notes 
The model is intended for English-language applications and could be adapted for other languages.
Supported Languages 
languages_supported (English), proficiency ()
Training Details 
Data Sources:
SlimPajama, UltraChat
Data Volume:
15 trillion tokens
Methodology:
Supervised fine-tuning, reinforcement learning with human feedback (RLHF)
Context Length:
262144
Hardware Used:
Crusoe Energy high performance L40S cluster
Model Architecture:
Transformer with improved RoPE theta, NTK-aware interpolation
Safety Evaluation 
Methodologies:
red teaming, adversarial evaluations
Risk Categories:
misinformation, bias, cybersecurity, child safety
Ethical Considerations:
Iterative testing for CBRNE threats
Responsible Ai Considerations 
Fairness:
Model is optimized for safety and helpfulness but trade-offs exist.
Transparency:
Steps for safety best practices outlined in Responsible Use Guide.
Accountability:
Meta
Mitigation Strategies:
Meta Llama Guard 2 and Code Shield provided for safety tailored applications
Input Output 
Input Format:
text input
Accepted Modalities:
text
Output Format:
text generation
Release Notes 
Version:
5/3/2024
Date:
2024-05-03
Notes:
Further fine-tuned for assistant-like chat ability; extended context length.
LLM NameGradientai Llama 3 8B Instruct 262k V2 EXL2 8.0bpw
Repository 🤗https://huggingface.co/bullerwins/gradientai_Llama-3-8B-Instruct-262k_v2_exl2_8.0bpw 
Model Size8b
Required VRAM8.4 GB
Updated2026-04-14
Maintainerbullerwins
Model Typellama
Instruction-BasedYes
Model Files  8.4 GB
Supported Languagesen
Quantization Typeexl2
Model ArchitectureLlamaForCausalLM
Licensellama3
Context Length262144
Model Max Length262144
Transformers Version4.41.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than bullerwins/gradientai_Llama-3-8B-Instruct-262k_v2_exl2_8.0bpw.

Rank the Gradientai Llama 3 8B Instruct 262K V2 EXL2 8.0bpw Capabilities

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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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