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Hyper X Qwen2 1.5B It Python by NuclearAi

 »  All LLMs  »  NuclearAi  »  Hyper X Qwen2 1.5B It Python   URL Share it on

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  1.5b   4-bit   4bit   Autotrain compatible Base model:quantized:qwen/qwen... Base model:qwen/qwen2-1.5b-ins...   Bitsandbytes   Conversational Dataset:nuclearai/nuke-python-...   En   Endpoints compatible   Instruct   Python   Quantized   Qwen2   Region:us   Safetensors   Sft
Model Card on HF 🤗: https://huggingface.co/NuclearAi/Hyper-X-Qwen2-1.5B-It-Python 

Hyper X Qwen2 1.5B It Python Benchmarks

LLME Score: 0.17697
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Hyper X Qwen2 1.5B It Python (NuclearAi/Hyper-X-Qwen2-1.5B-It-Python)

Hyper X Qwen2 1.5B It Python Parameters and Internals

Model Type 
text-generation, transformers
Additional Notes 
Model is specifically tuned for Python code generation.
Training Details 
Data Sources:
NuclearAi/Nuke-Python-Verse
Data Volume:
240,888 unique lines of Python codes
Methodology:
finetuned from Qwen2-1.5B-Instruct
Input Output 
Accepted Modalities:
text
Output Format:
text
LLM NameHyper X Qwen2 1.5B It Python
Repository 🤗https://huggingface.co/NuclearAi/Hyper-X-Qwen2-1.5B-It-Python 
Base Model(s)  Qwen/Qwen2-1.5B-Instruct   Qwen/Qwen2-1.5B-Instruct
Model Size1.5b
Required VRAM1.1 GB
Updated2025-03-31
MaintainerNuclearAi
Model Typeqwen2
Instruction-BasedYes
Model Files  1.1 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than NuclearAi/Hyper-X-Qwen2-1.5B-It-Python.

Rank the Hyper X Qwen2 1.5B It Python 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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