--- datasets: - ehartford/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split - jondurbin/airoboros-gpt4-1.4.1 - openai/summarize_from_feedback - ehartford/wizard_vicuna_70k_unfiltered language: - en tags: - llama --- Trained on a flavorful melange of the WizardLM, Airoboros, and Wizard Vicuna datasets. This model was trained using both linear and NTK-aware RoPE scaling in tandem. When loading, ensure that `compress_pos_emb` (or `scale`) is set to 2, and `alpha_value` is set to 4. *Both* values must be set. Expect context length of up to 8192 to work for sure. It will probably maintain coherence into the ~12k range, but I have not tested that. Prompt format is vicuna 1.1: ``` USER: ... ASSISTANT: ... ```