Robin 7B V2 SuperHOT 8K Fp16 by TheBloke

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  Autotrain compatible   Custom code   Ext 8k   Fp16   Llama   Pytorch   Quantized   Region:us   Sharded

Robin 7B V2 SuperHOT 8K Fp16 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Robin 7B V2 SuperHOT 8K Fp16 (TheBloke/Robin-7B-v2-SuperHOT-8K-fp16)
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Robin 7B V2 SuperHOT 8K Fp16 Parameters and Internals

Model Type 
text generation, multimodal
Additional Notes 
The model has been merged with Kaio Ken's SuperHOT 8K for extended context usage.
Training Details 
Context Length:
8192
Hardware Used:
4-bit base model for training
Model Architecture:
LoRA model implementation
Input Output 
Input Format:
A chat between a curious human and an artificial intelligence assistant.
Accepted Modalities:
text
Output Format:
Detailed, polite answers to the human's questions
Performance Tips:
For 8K context length, set 'config.max_position_embeddings' to 8192 and use 'trust_remote_code=True'
LLM NameRobin 7B V2 SuperHOT 8K Fp16
Repository ๐Ÿค—https://huggingface.co/TheBloke/Robin-7B-v2-SuperHOT-8K-fp16 
Model Size7b
Required VRAM13.5 GB
Updated2025-08-18
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   3.5 GB: 2-of-2
Context Length8k
Quantization Typefp16
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.30.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Robin-7B-v2-SuperHOT-8K-fp16.

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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  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124