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Brucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2 by MarinaraSpaghetti

 »  All LLMs  »  MarinaraSpaghetti  »  Brucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2   URL Share it on

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  Arxiv:2306.01708   Arxiv:2311.03099   Autotrain compatible   En   Endpoints compatible   Exl2   Exllama   Exllamav2   Llama   Merge   Mergekit   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Yi
Model Card on HF 🤗: https://huggingface.co/MarinaraSpaghetti/brucethemoose_Yi-34B-200K-RPMerge-4.65bpw-h6-exl2 

Brucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2 Benchmarks

LLME Score: 0.18008
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Brucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2 (MarinaraSpaghetti/brucethemoose_Yi-34B-200K-RPMerge-4.65bpw-h6-exl2)

Brucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2 Parameters and Internals

Model Type 
text generation, instruct-enhanced storytelling
Use Cases 
Areas:
Storytelling, Instruct-enhanced tasks
Applications:
Long-context writing, Roleplaying scenarios
Primary Use Cases:
40K+ context instruct-enhanced storytelling
Limitations:
Some quirks due to token/instruct formats
Considerations:
Careful parameter tuning required for optimal performance.
Additional Notes 
This model is a merge of several Yi 34B models to achieve specific performance goals, especially for storytelling.
Supported Languages 
en (High)
Training Details 
Data Sources:
Roleplaying data, Vicuna-format data, Alpaca format data
Data Volume:
200K tokens
Methodology:
DARE TIES merge method
Context Length:
40000
Hardware Used:
24GB GPUs
Model Architecture:
Yi 34B with Vicuna-format emphasis
Input Output 
Input Format:
Orca-Vicuna
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use lower temperature settings and additional sampling techniques for best performance.
Release Notes 
Notes:
Initial release focusing on instruct-enhanced storytelling at 40K+ context.
LLM NameBrucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2
Repository 🤗https://huggingface.co/MarinaraSpaghetti/brucethemoose_Yi-34B-200K-RPMerge-4.65bpw-h6-exl2 
Model Size34b
Required VRAM10.5 GB
Updated2024-12-22
MaintainerMarinaraSpaghetti
Model Typellama
Model Files  8.6 GB: 1-of-2   1.9 GB: 2-of-2
Supported Languagesen
Quantization Typeexl2
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length200000
Model Max Length200000
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than MarinaraSpaghetti/brucethemoose_Yi-34B-200K-RPMerge-4.65bpw-h6-exl2.

Rank the Brucethemoose Yi 34B 200K RPMerge 4.65bpw H6 EXL2 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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Release v20241217
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