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Open-source mixed-deu-ell-sequential_interleaved model from nikitastheo — available for download and self-hosting on Hugging Face.
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Local run command
pip install transformers accelerate && python -c "from transformers import AutoModelForCausalLM, AutoTokenizer; tok = AutoTokenzier.from_pretrained('nikitastheo/mixed-deu-ell-sequential_interleaved'); model = AutoModelForCausalLM.from_pretrained('nikitastheo/mixed-deu-ell-sequential_interleaved'); print('Loaded nikitastheo/mixed-deu-ell-sequential_interleaved')"Presumptive Specs:
Community reliability estimate · not official
About this score: Community-estimated based on user reports and publicly available benchmark data (e.g. TruthfulQA). This is not an official score from the model provider. Scores may be inaccurate — always verify with the official leaderboard before making production decisions.
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Provider
Learn how to use mixed-deu-ell-sequential_interleaved
💡 Tip: Start with the sample prompts above to see how mixed-deu-ell-sequential_interleaved works best.
Proven prompts shared by the community for this model