Qwen2.5 0.5B OpenHermes2.5 by artificialguybr

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  Autotrain compatible Base model:finetune:qwen/qwen2...   Base model:qwen/qwen2.5-0.5b   Conversational   Dataset:teknium/openhermes-2.5   Endpoints compatible   Generated from trainer   Pytorch   Qwen2   Region:us

Qwen2.5 0.5B OpenHermes2.5 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen2.5 0.5B OpenHermes2.5 (artificialguybr/Qwen2.5-0.5B-OpenHermes2.5)

Qwen2.5 0.5B OpenHermes2.5 Parameters and Internals

Model Type 
Causal Language Model
Use Cases 
Primary Use Cases:
Research in NLP tasks, Text generation, Language understanding, Conversational AI
Limitations:
Not recommended for direct use in conversations without further fine-tuning, Performance may vary across languages and domains, Potential biases in the training data
Additional Notes 
The base Qwen2.5-0.5B model has enhanced capabilities in coding, mathematics, and understanding structured data. It supports long-context processing up to 128K tokens.
Supported Languages 
Multilingual support (>29)
Training Details 
Data Volume:
1 million samples
Context Length:
32768
Model Architecture:
Transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias, and tied word embeddings
LLM NameQwen2.5 0.5B OpenHermes2.5
Repository ๐Ÿค—https://huggingface.co/artificialguybr/Qwen2.5-0.5B-OpenHermes2.5 
Base Model(s)  Qwen/Qwen2.5-0.5B   Qwen/Qwen2.5-0.5B
Model Size0.5b
Required VRAM1.3 GB
Updated2025-02-22
Maintainerartificialguybr
Model Typeqwen2
Model Files  1.3 GB
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.45.0.dev0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than artificialguybr/Qwen2.5-0.5B-OpenHermes2.5.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227