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README.md
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@@ -48,12 +48,12 @@ Chosen subsets of the 91 billion corpus were upsampled resulting in a size of **
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Llama-Krikri-8B-Instruct is the result of post-training Llama-Kriki-8B-Base and features:
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- Enhanced chat capabilities and instruction-following in both Greek and English.
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- Document translation from Greek to English, French, German, Italian, Portuguese, Spanish and vice versa.
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- Domain-specifc expertise for specialized legal, financial, medical, and scientific applications.
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- Great performance on generation, comprehension, and editing tasks, such as summarization, creative content creation, text modification, entity recognition, sentiment analysis, etc.
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- Retrieval-Augmented Generation (RAG) utilizing multiple documents with 128k context length.
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- Improved coding and agentic capabilities with correct formatting and tool use.
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- Conversion or structured extraction (e.g., XML, JSON) in data-to-text & text-to-data settings.
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- Analytical thinking and Chain-of-Thought (CoT) reasoning for problem-
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🚨 **More information on the post-training corpus and methdology coming soon.** 🚨
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Llama-Krikri-8B-Instruct is the result of post-training Llama-Kriki-8B-Base and features:
|
49 |
- Enhanced chat capabilities and instruction-following in both Greek and English.
|
50 |
- Document translation from Greek to English, French, German, Italian, Portuguese, Spanish and vice versa.
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51 |
- Great performance on generation, comprehension, and editing tasks, such as summarization, creative content creation, text modification, entity recognition, sentiment analysis, etc.
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+
- Domain-specifc expertise for specialized legal, financial, medical, and scientific applications.
|
53 |
- Retrieval-Augmented Generation (RAG) utilizing multiple documents with 128k context length.
|
54 |
- Improved coding and agentic capabilities with correct formatting and tool use.
|
55 |
- Conversion or structured extraction (e.g., XML, JSON) in data-to-text & text-to-data settings.
|
56 |
+
- Analytical thinking and Chain-of-Thought (CoT) reasoning for problem-solving.
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57 |
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58 |
🚨 **More information on the post-training corpus and methdology coming soon.** 🚨
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