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Tiiuae Falcon 7B Instruct W4 G64 AWQ by abhinavkulkarni

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Tiiuae Falcon 7B Instruct W4 G64 AWQ is an open-source language model by abhinavkulkarni. Features: 7b LLM, VRAM: 4.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.08.

  Awq   Custom code   Instruct   Pytorch   Quantized   Refinedwebmodel   Region:us
Model Card on HF 🤗: https://huggingface.co/abhinavkulkarni/tiiuae-falcon-7b-instruct-w4-g64-awq 

Tiiuae Falcon 7B Instruct W4 G64 AWQ Benchmarks

LLME Score: 0.07869
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Tiiuae Falcon 7B Instruct W4 G64 AWQ (abhinavkulkarni/tiiuae-falcon-7b-instruct-w4-g64-awq)
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Tiiuae Falcon 7B Instruct W4 G64 AWQ Parameters and Internals

Model Type 
causal_decoder
Additional Notes 
4-bit 64-group size AWQ quantized model for efficient inference.
Training Details 
Methodology:
Finetuned on a mixture of chat/instruct datasets
Input Output 
Accepted Modalities:
text
LLM NameTiiuae Falcon 7B Instruct W4 G64 AWQ
Repository 🤗https://huggingface.co/abhinavkulkarni/tiiuae-falcon-7b-instruct-w4-g64-awq 
Model Size7b
Required VRAM4.2 GB
Updated2026-06-19
Maintainerabhinavkulkarni
Model TypeRefinedWebModel
Instruction-BasedYes
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureRWForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.33.1
Is Biased0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size65024
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than abhinavkulkarni/tiiuae-falcon-7b-instruct-w4-g64-awq.

Rank the Tiiuae Falcon 7B Instruct W4 G64 AWQ 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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