Sft Model by AravindS373

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  4bit   Autotrain compatible   Codegen   Conversational   En   Endpoints compatible   Instruct   Quantized   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF ๐Ÿค—: https://huggingface.co/AravindS373/sft_model 

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").
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Sft Model Parameters and Internals

LLM NameSft Model
Repository ๐Ÿค—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
Updated2025-06-09
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
Sft Model (AravindS373/sft_model)

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FastApply 7B V1.032K / 15.2 GB74431
Qwen2.5 Coder 7B Instruct 4bit32K / 4.3 GB5615
...en2.5.1 Coder 7B Instruct 8bit32K / 8.1 GB382
...en2.5.1 Coder 7B Instruct 4bit32K / 4.3 GB333
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Qwen2.5 7B Rebase986K / 15.2 GB102
StockQwen 2.5 7B128K / 15.2 GB505
Note: green Score (e.g. "73.2") means that the model is better than AravindS373/sft_model.

Rank the Sft Model 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124