Sft Model by AravindS373

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Sft Model is an open-source language model by AravindS373. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.19.

  4bit   Autotrain compatible   Codegen   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth

Sft Model Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Sft Model Parameters and Internals

LLM NameSft Model
Repository 🤗https://huggingface.co/AravindS373/sft_model 
Base Model(s)  unsloth/qwen2.5-coder-7b-instruct-bnb-4bit   unsloth/qwen2.5-coder-7b-instruct-bnb-4bit
Model Size7b
Required VRAM15.2 GB
Updated2025-09-19
MaintainerAravindS373
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4
Supported Languagesen
Quantization Type4bit
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.51.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to Sft Model

Best Alternatives
Context / RAM
Downloads
Likes
Securereview 7B Mlx 4bit32K / 4.3 GB152
...2.5 Coder 7B Instruct Bnb 4bit32K / 5.5 GB6791312
Qwen2.5 CoderX 7B V0.732K / 15.2 GB132
Qwen2.5 CoderX 7B V0.532K / 15.2 GB92
Qwen2.5 Coder 7B Instruct 4bit32K / 4.3 GB490811
UIGEN 7B 16bit32K / 15.2 GB85
...en2.5.1 Coder 7B Instruct 4bit32K / 4.3 GB6533
...en2.5.1 Coder 7B Instruct 8bit32K / 8.1 GB1563
FastApply 7B V1.032K / 15.2 GB14637
Qwen2.5 7B Rebase986K / 15.2 GB732
Note: green Score (e.g. "73.2") means that the model is better than AravindS373/sft_model.

Rank the Sft Model 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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Release v20260328a