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Coder1.8 ORPO TEST by raincandy-u

 »  All LLMs  »  raincandy-u  »  Coder1.8 ORPO TEST   URL Share it on

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  Autotrain compatible   Code   Conversational Dataset:reciprocate/dpo ultra-...   En   Endpoints compatible   Model-index   Qwen2   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/raincandy-u/Coder1.8-ORPO-TEST 

Coder1.8 ORPO TEST Benchmarks

ARC: 38.82 vs 96.7 (so35)-59.9%
HellaSwag: 60.48 vs 95.3 (gpt4)-36.5%
MMLU: 46.7 vs 88.3 (so35)-47.1%
TruthfulQA: 41.38 vs 59 (gpt4)-29.9%
WinoGrande: 59.75 vs 87.5 (gpt4)-31.7%
GSM8K: 27.45 vs 96.4 (so35)-71.5%
LLME Score: 0.20947
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Coder1.8 ORPO TEST (raincandy-u/Coder1.8-ORPO-TEST)

Coder1.8 ORPO TEST Parameters and Internals

Model Type 
text-generation
Use Cases 
Limitations:
Limited training data and quantization may impact performance.
Additional Notes 
This is a test model and may generate incorrect responses. Use at your own risk.
Training Details 
Data Sources:
reciprocate/dpo_ultra-capybara-code_filtered-best
Data Volume:
~20k code examples
Methodology:
ORPO
Training Time:
1 epoch
Hardware Used:
2 x A40
LLM NameCoder1.8 ORPO TEST
Repository 🤗https://huggingface.co/raincandy-u/Coder1.8-ORPO-TEST 
Model Size1.8b
Required VRAM3.7 GB
Updated2025-03-24
Maintainerraincandy-u
Model Typeqwen2
Model Files  3.7 GB
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length32768
Model Max Length32768
Transformers Version4.39.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than raincandy-u/Coder1.8-ORPO-TEST.

Rank the Coder1.8 ORPO TEST 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 v20241227
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