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Redmond Hermes Coder GPTQ by TheBloke

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Model Card on HF 🤗: https://huggingface.co/TheBloke/Redmond-Hermes-Coder-GPTQ 

Redmond Hermes Coder GPTQ Benchmarks

LLME Score: 0.09223
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Redmond Hermes Coder GPTQ (TheBloke/Redmond-Hermes-Coder-GPTQ)
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Redmond Hermes Coder GPTQ Parameters and Internals

Model Type 
text generation, language model
Use Cases 
Areas:
Research, Commercial applications
Applications:
Text generation, Understanding complex instructions, Code generation, Creative writing
Limitations:
Worse performance than WizardCoder on pure code benchmarks
Additional Notes 
The model was fine-tuned almost entirely on synthetic GPT-4 outputs.
Supported Languages 
en (Full)
Training Details 
Data Sources:
GPTeacher, general, roleplay v1&2, code instruct datasets, Nous Instruct & PDACTL, CodeAlpaca, Evol_Instruct Uncensored, GPT4-LLM, Unnatural Instructions, Camel-AI's Biology/Physics/Chemistry, Math Datasets, Airoboros' GPT-4 Dataset
Data Volume:
Over 300,000 instructions
Methodology:
Fine-tuning using WizardCoder base, primarily on synthetic GPT-4 outputs
Input Output 
Input Format:
Alpaca format: '### Instruction: ### Response:'
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use the recommended setup for optimal performance.
LLM NameRedmond Hermes Coder GPTQ
Repository 🤗https://huggingface.co/TheBloke/Redmond-Hermes-Coder-GPTQ 
Model Size2.7b
Required VRAM9.2 GB
Updated2025-09-23
MaintainerTheBloke
Model Typegpt_bigcode
Model Files  9.2 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq
Generates CodeYes
Model ArchitectureGPTBigCodeForCausalLM
Licensegpl
Model Max Length2048
Transformers Version4.29.2
Tokenizer ClassGPT2Tokenizer
Vocabulary Size49153
Torch Data Typefloat16
Activation Functiongelu

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Redmond-Hermes-Coder-GPTQ.

Rank the Redmond Hermes Coder GPTQ 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 v20241124
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