Duloxetine 4B V1 by Fizzarolli

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Duloxetine 4B V1 is an open-source language model by Fizzarolli. Features: 4b LLM, VRAM: 7.9GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.14.

  Autotrain compatible   Axolotl   Conversational   Dataset:abacusai/systemchat   Dataset:fizzarolli/wattpad Dataset:grimulkan/theory-of-mi... Dataset:huggingfaceh4/no robot... Dataset:minervaai/aesir-previe... Dataset:sao10k/claude-3-opus-i...   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow

Duloxetine 4B V1 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Duloxetine 4B V1 (Fizzarolli/duloxetine-4b-v1)
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Duloxetine 4B V1 Parameters and Internals

Model Type 
text generation, roleplaying
Use Cases 
Primary Use Cases:
fast roleplay
Supported Languages 
language_codes (en), proficiency (unknown)
Input Output 
Input Format:
chatml
LLM NameDuloxetine 4B V1
Repository ๐Ÿค—https://huggingface.co/Fizzarolli/duloxetine-4b-v1 
Model Size4b
Required VRAM7.9 GB
Updated2025-11-04
MaintainerFizzarolli
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.9 GB: 2-of-2
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.41.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Duloxetine 4B V1

Best Alternatives
Context / RAM
Downloads
Likes
Qwarkstar 4B Instruct Preview32K / 9 GB82
Qwarkstar 4B Instruct32K / 9 GB301
Nusantara 4B Indo Chat32K / 7.9 GB1242
Sailor 4B Chat32K / 7.9 GB1602
Qwen1.5 4B Chat Paraph32K / 7.9 GB80
Note: green Score (e.g. "73.2") means that the model is better than Fizzarolli/duloxetine-4b-v1.

Rank the Duloxetine 4B V1 Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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 v20260328a