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Qwen2.5 1.5B Instruct Legal Chatbot Sft by galnoel

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Qwen2.5 1.5B Instruct Legal Chatbot Sft is an open-source language model by galnoel. Features: 1.5b LLM, VRAM: 3.1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.3.

  4bit Base model:finetune:unsloth/qw... Base model:unsloth/qwen2.5-1.5...   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Unsloth
Model Card on HF 🤗: https://huggingface.co/galnoel/qwen2.5-1.5b-instruct-legal-chatbot-sft 

Qwen2.5 1.5B Instruct Legal Chatbot Sft Benchmarks

LLME Score: 0.30497
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 1.5B Instruct Legal Chatbot Sft (galnoel/qwen2.5-1.5b-instruct-legal-chatbot-sft)
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Qwen2.5 1.5B Instruct Legal Chatbot Sft Parameters and Internals

LLM NameQwen2.5 1.5B Instruct Legal Chatbot Sft
Repository 🤗https://huggingface.co/galnoel/qwen2.5-1.5b-instruct-legal-chatbot-sft 
Base Model(s)  unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit   unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit
Model Size1.5b
Required VRAM3.1 GB
Updated2026-07-22
Maintainergalnoel
Model Typeqwen2
Instruction-BasedYes
Model Files  3.1 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Tokenizer ClassQwen2Tokenizer
Padding Token<|vision_pad|>
Vocabulary Size151936
Torch Data Typefloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than galnoel/qwen2.5-1.5b-instruct-legal-chatbot-sft.

Rank the Qwen2.5 1.5B Instruct Legal Chatbot Sft 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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