Ahma 3B by Finnish-NLP

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  Arxiv:2302.06675   Arxiv:2302.13971   Arxiv:2305.16264   Autotrain compatible   Conversational Dataset:finnish-nlp/culturax f... Dataset:finnish-nlp/hplt 1.2 f... Dataset:finnish-nlp/reddit fi ... Dataset:finnish-nlp/wikipedia ... Dataset:intfloat/multilingual ...   Doi:10.57967/hf/4011   Fi   Finnish   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF πŸ€—: https://huggingface.co/Finnish-NLP/Ahma-3B 

Ahma 3B Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ahma 3B (Finnish-NLP/Ahma-3B)

Ahma 3B Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research, Commercial applications
Primary Use Cases:
Text generation, Fine-tuning for downstream tasks
Limitations:
Not suitable for multilingual use, Biased predictions due to training data characteristics, Cannot generate code
Considerations:
Can benefit from fine-tuning for instruction following
Additional Notes 
Utilizes 2-stage pretraining approach to boost instruction-following capabilities.
Supported Languages 
fi (native)
Training Details 
Data Sources:
Finnish-NLP/CulturaX_fi_cleaned, Finnish-NLP/HPLT_1.2_fi_cleaned, Finnish-NLP/wikipedia_20231101_fi_cleaned, Finnish-NLP/Reddit_fi_2006_2022, Yle Finnish News Archive 2011-2018, Yle Finnish News Archive 2019-2020, Finnish News Agency Archive (STT), The Suomi24 Sentences Corpus, Project LΓΆnnrot, Finnish parliament speeches, multilingual_cc_news, fi-news-corpus, Finnish higher education public theses, Finnish single-turn instruction-following datasets
Data Volume:
23 billion words
Methodology:
Pretrained on Finnish language, resampling and filtering techniques used, included instruction-following examples mixed in.
Context Length:
2048
Training Time:
N/A
Hardware Used:
TPUv4-32
Model Architecture:
3B parameter, decoder-only transformer
Input Output 
Input Format:
Tokenized text input as structured prompts with context.
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Utilize optimal generation settings like repetition penalty, and proper prompt formatting.
Release Notes 
Version:
N/A
Date:
N/A
Notes:
Model checkpoints were pushed every 100,000 training steps.
LLM NameAhma 3B
Repository πŸ€—https://huggingface.co/Finnish-NLP/Ahma-3B 
Model Size3b
Required VRAM7.3 GB
Updated2025-04-23
MaintainerFinnish-NLP
Model Typellama
Model Files  5.0 GB: 1-of-2   2.3 GB: 2-of-2
Supported Languagesfi
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.42.0.dev0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size64256
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than Finnish-NLP/Ahma-3B.

Rank the Ahma 3B Capabilities

πŸ†˜ 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