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TinyStoriesChinese 110M by fzmnm

 »  All LLMs  »  fzmnm  »  TinyStoriesChinese 110M   URL Share it on

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  Arxiv:2203.15556   Autotrain compatible Dataset:adam89/tinystorieschin...   Endpoints compatible   Llama   Pytorch   Region:us   Zh
Model Card on HF 🤗: https://huggingface.co/fzmnm/TinyStoriesChinese-110M 

TinyStoriesChinese 110M Benchmarks

LLME Score: 0.15626
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyStoriesChinese 110M (fzmnm/TinyStoriesChinese-110M)
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TinyStoriesChinese 110M Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Educational purposes, Machine learning training for beginners
Applications:
Generation of short Chinese stories
Primary Use Cases:
Text generation for educational tools
Limitations:
Consistency and depth of logical capabilities vary
Considerations:
Focused on simple, narrowly defined tasks; ideal for experimentation
Additional Notes 
Demonstrates potential of smaller models to produce coherent text without extensive computational resources.
Supported Languages 
zh (Proficient)
Training Details 
Data Sources:
adam89/TinyStoriesChinese
Data Volume:
2G tokens
Methodology:
Standard llama2 format Transformer with 12 layers, 12 attention heads, and a hidden size of 768. The model utilizes a 1024 context window with Relative Positional Encodings (RoPE) and a vocabulary size of 5,000.
Context Length:
1024
Training Time:
87 hours
Hardware Used:
NVIDIA RTX 2080 Super with 8 GB RAM
Model Architecture:
Standard llama2 format Transformer
Input Output 
Input Format:
Text prompt
Accepted Modalities:
text
Output Format:
Generated story text
LLM NameTinyStoriesChinese 110M
Repository 🤗https://huggingface.co/fzmnm/TinyStoriesChinese-110M 
Model Size110m
Required VRAM0.4 GB
Updated2025-09-23
Maintainerfzmnm
Model Typellama
Model Files  0.4 GB
Supported Languageszh
Model ArchitectureLlamaForCausalLM
Licensecc
Context Length1024
Model Max Length1024
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size5000

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Note: green Score (e.g. "73.2") means that the model is better than fzmnm/TinyStoriesChinese-110M.

Rank the TinyStoriesChinese 110M 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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