mags0ft/SmolLM2-360m-German-Instruct
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Author SHA1 Message Date
Magnus
e4095399dd correct wrong percentage of German Wikipedia pre-training info in README 2025-10-05 11:07:22 +00:00
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fa31b5a5d7 Upload f16/F16.gguf with huggingface_hub 2025-07-20 00:22:47 +00:00
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06d9b60a91 Upload q4_k_m/Q4_K_M.gguf with huggingface_hub 2025-07-20 00:17:12 +00:00
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4b18e5b9d6 again, restore README 2025-07-20 00:11:12 +00:00
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aa4c27b3a1 (Trained with Unsloth) 2025-07-20 00:09:36 +00:00
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5f284aa418 Unsloth Model Card 2025-07-20 00:04:47 +00:00
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c861aad2ef Upload showcase-image.png 2025-07-19 23:46:54 +00:00
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0e16271f54 Delete showcase-image.png 2025-07-19 23:46:46 +00:00
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2f38f7051e add showcase image to README 2025-07-19 23:45:22 +00:00
6 changed files with 11 additions and 8 deletions
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README.md
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@@ -11,11 +11,14 @@ datasets:
- wikimedia/wikipedia - wikimedia/wikipedia
- FreedomIntelligence/alpaca-gpt4-deutsch - FreedomIntelligence/alpaca-gpt4-deutsch
--- ---
# SmolLM2-360m-German-Instruct # SmolLM2-360m-German-Instruct
<p align="center">
<img alt="Showcase image for SmolLM2-360m-German-Instruct" src="https://huggingface.co/mags0ft/SmolLM2-360m-German-Instruct/resolve/main/showcase-image.png" width="600" />
</p>
This is a continued pre-train as well as an instruct fine-tune done using Unsloth in order to make SmolLM2 360m capable of speaking German. This is a continued pre-train as well as an instruct fine-tune done using Unsloth in order to make SmolLM2 360m capable of speaking German.
It has been trained on 15% of the German Wikipedia as well as the full German version of the Alpaca-GPT4 dataset (translated version). It has been trained on 25% of the German Wikipedia as well as the full German version of the Alpaca-GPT4 dataset (translated version).
Even though a lot of training has been done, this is still a tiny model and is highly limited to its small size. Expect many hallucinations and do not use this in a demanding production workflow. Even though a lot of training has been done, this is still a tiny model and is highly limited to its small size. Expect many hallucinations and do not use this in a demanding production workflow.

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