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Yi 34B 200K RPMerge AWQ by LoneStriker

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Yi 34B 200K RPMerge AWQ is an open-source language model by LoneStriker. Features: 34b LLM, VRAM: 19.2GB, Context: 195K, License: other, Quantized, LLM Explorer Score: 0.12.

  Arxiv:2306.01708   Arxiv:2311.03099   4-bit   Awq   En   Endpoints compatible   Exl2   Exllama   Exllamav2   Llama   Merge   Mergekit   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Yi
Model Card on HF 🤗: https://huggingface.co/LoneStriker/Yi-34B-200K-RPMerge-AWQ 

Yi 34B 200K RPMerge AWQ Benchmarks

LLME Score: 0.11852
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Yi 34B 200K RPMerge AWQ (LoneStriker/Yi-34B-200K-RPMerge-AWQ)
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Yi 34B 200K RPMerge AWQ Parameters and Internals

Model Type 
storytelling, instruction-following
Use Cases 
Areas:
storytelling, creative writing, role-playing
Applications:
novel writing, interactive fiction
Primary Use Cases:
>40K context, instruct-enhanced storytelling
Additional Notes 
Tested for novel-style continuation, assistant-type responses, and long context analysis without refusals. Specific to certain configurations for performance of storytelling in longer contexts.
Supported Languages 
en (proficient)
Training Details 
Data Sources:
DrNicefellow/ChatAllInOne-Yi-34B-200K-V1, migtissera/Tess-34B-v1.5b, cgato/Thespis-34b-v0.7, Doctor-Shotgun/limarpv3-yi-llama-34b-lora, adamo1139/yi-34b-200k-rawrr-dpo-2, migtissera/Tess-M-Creative-v1.0, NousResearch/Nous-Capybara-34B
Methodology:
Merge using DARE (Discrete Alignment-based Row Expansion) technique
Context Length:
40000
Input Output 
Input Format:
SYSTEM: {system_message} USER: {prompt} ASSISTANT:
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Running Chinese models with large tokenizer vocabularies like Yi need careful parameter tuning due to large logit sampling tails.
LLM NameYi 34B 200K RPMerge AWQ
Repository 🤗https://huggingface.co/LoneStriker/Yi-34B-200K-RPMerge-AWQ 
Model Size34b
Required VRAM19.2 GB
Updated2026-04-12
MaintainerLoneStriker
Model Typellama
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   4.3 GB: 4-of-4
Supported Languagesen
AWQ QuantizationYes
Quantization Typeexl2|awq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length200000
Model Max Length200000
Transformers Version4.37.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64002
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Yi-34B-200K-RPMerge-AWQ.

Rank the Yi 34B 200K RPMerge AWQ 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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