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Open-source carbonated_sft_adapter model from satya-sri — 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('satya-sri/carbonated_sft_adapter'); model = AutoModelForCausalLM.from_pretrained('satya-sri/carbonated_sft_adapter'); print('Loaded satya-sri/carbonated_sft_adapter')"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 carbonated_sft_adapter
💡 Tip: Start with the sample prompts above to see how carbonated_sft_adapter works best.
Proven prompts shared by the community for this model