68 lines
2.3 KiB
Markdown
68 lines
2.3 KiB
Markdown
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---
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license: apache-2.0
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datasets:
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- LTS-VVE/Teuta-sq
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- LTS-VVE/grammar_sq_0.1
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- LTS-VVE/linguistic_sq
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- LTS-VVE/Math-physics-dataset-sq
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- LTS-VVE/albanian-synthetic
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- noxneural/lilium_albanicum_eng_alb
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- MIND-Lab/Safety-Evaluation
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- shb777/simple-math-steps-7M
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- RishiKompelli/TherapyDataset
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- microsoft/orca-math-word-problems-200k
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- Vezora/Tested-143k-Python-Alpaca
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- AI4Chem/ChemPref-DPO-for-Chemistry-data-en
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- jkhedri/psychology-dataset
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- samhog/psychology-10k
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- Amod/mental_health_counseling_conversations
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- sayhan/strix-philosophy-qa
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- Maverfrick/Rust_dataset
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- Neloy262/rust_instruction_dataset
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- Tesslate/Rust_Dataset
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language:
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- en
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- sq
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base_model:
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- meta-llama/Llama-3.2-3B
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pipeline_tag: text-generation
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tags:
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- al
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- math
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- philosophy
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- chemistry
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- code
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- biology
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- climate
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- not-for-all-audiences
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---
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<p align="center">
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<span style="color:yellow">This model is not suitable for all audiences and may contain inappropriate or explicit content.</span>
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</p>
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/67b7476deb48853c39ca000b/CzUTg97aTxK283qwD6kEm.png" alt="Teuta Logo" />
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</p>
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# Teuta (A work in progress!)
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Teuta is a bilingual instruction-tuned language model designed for question answering in both Albanian (sq) and English (en). It is fine-tuned on a diverse mix of datasets covering subjects such as mathematics, philosophy, chemistry, biology, code (especially Rust), psychology, and climate science.
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## Model
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- **Base model**: meta-llama/Llama-3.2-3B
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- **Languages**: Albanian, English
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- **Primary task**: Instruction-following and question answering
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## Description
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Teuta is built to handle a variety of instructional prompts, from academic and scientific queries to more open-ended tasks. It is particularly suited for multilingual applications and under-resourced language support, with a strong focus on Albanian.
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The model leverages both synthetic and real datasets to improve generalization across technical and non-technical domains.
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## Considerations
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- Some datasets include sensitive content (e.g., mental health, therapy, and philosophical questions).
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- Outputs are not guaranteed to be factual or safe; use in sensitive contexts should be done with care.
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- Best suited for research, educational tools, and domain-specific applications.
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