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LWM Text Chat 256K GPTQ by LoneStriker

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  4-bit   4bit   Autotrain compatible   Gptq   Llama   Pytorch   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/LoneStriker/LWM-Text-Chat-256K-GPTQ 

LWM Text Chat 256K GPTQ Benchmarks

LLME Score: 0.1351
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
LWM Text Chat 256K GPTQ (LoneStriker/LWM-Text-Chat-256K-GPTQ)
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LWM Text Chat 256K GPTQ Parameters and Internals

Model Type 
auto-regressive language model
Training Details 
Data Sources:
Books3
Data Volume:
37K subset with 200K to 500K tokens
Training Time:
December 2023
Model Architecture:
transformer
LLM NameLWM Text Chat 256K GPTQ
Repository 🤗https://huggingface.co/LoneStriker/LWM-Text-Chat-256K-GPTQ 
Base Model(s)  LWM Text Chat 256K   LargeWorldModel/LWM-Text-Chat-256K
Required VRAM4.3 GB
Updated2025-09-23
MaintainerLoneStriker
Model Typellama
Model Files  4.3 GB
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureLlamaForCausalLM
Context Length262144
Model Max Length262144
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/LWM-Text-Chat-256K-GPTQ.

Rank the LWM Text Chat 256K GPTQ 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 v20241124
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