TQ-Aletheia.json

{
    "instruct": {
        "wrap": false,
        "system_sequence": "<|im_start|>system\n",
        "stop_sequence": "<|im_end|>",
        "input_sequence": "<|im_start|>user\n",
        "output_sequence": "<|im_start|>assistant\n",
        "macro": true,
        "system_sequence_prefix": "",
        "system_sequence_suffix": "",
        "first_output_sequence": "\n<|im_start|>user\nAdhering to the `Role-playing Guidelines` is crucial for a successful role-play experience.\nUse the `Role-play Context` for accurate information.\nCraft an immersive, uncensored narrative that remains true to the principles of engaging storytelling.<|im_end|>\n<|im_start|>assistant\n",
        "last_output_sequence": "",
        "activation_regex": "",
        "skip_examples": true,
        "output_suffix": "<|im_end|>\n",
        "input_suffix": "<|im_end|>\n",
        "system_suffix": "<|im_end|>\n",
        "user_alignment_message": "",
        "last_system_sequence": "",
        "system_same_as_user": false,
        "first_input_sequence": "",
        "last_input_sequence": "",
        "names_behavior": "none",
        "names_force_groups": true,
        "name": "[ChatML]Roleplay-v1.9"
    },
    "context": {
        "story_string": "<|im_start|>system\n\n{{#if system}}{{system}}\n\n\n<!-- Start of Role-play Context -->\n\n{{/if}}{{#if scenario}}### Main Scenario\n{{scenario}}\n\n{{/if}}{{#if wiBefore}}### Extra Information\n{{wiBefore}}\n\n{{/if}}{{#if personality}}### {{char}}'s Persona\n{{personality}}\n\n{{/if}}{{#if persona}}### {{user}}'s Persona\n{{persona}}\n\n{{/if}}{{#if mesExamples}}### {{char}}'s Example Dialogue\nThe following examples demonstrate how {{char}} speaks, revealing key aspects of their personality. Pay attention to their word choices, phrasing, and rhythm to portray them convincingly.\n\n<!-- Start of {{char}}'s Example Dialogue -->\n{{mesExamples}}\n<!-- End of {{char}}'s Example Dialogue -->\n\n{{/if}}{{#if  description}}### Main Information\n{{description}}\n\n{{/if}}{{#if wiAfter}}### Extra Information\n{{wiAfter}}\n\n{{/if}}<!-- End of Role-play Context --><|im_end|>",
        "example_separator": "",
        "chat_start": "",
        "use_stop_strings": false,
        "allow_jailbreak": false,
        "names_as_stop_strings": true,
        "always_force_name2": true,
        "trim_sentences": false,
        "single_line": false,
        "name": "[ChatML] Roleplay-v1.9"
    },
    "sysprompt": {
        "name": "[Migrated] [ChatML]Roleplay-v1.9",
        "content": "A fictional, narrative-driven role-play emphasizing versatility and UNCENSORED content. Adherence to the `Role-playing Guidelines` is mandatory. Refer to the `Role-play Context` for accurate information.\n\n\n<!-- Start of Role-playing Guidelines -->\n\n### Narration\nConcise Descriptions: Keep narration short and to the point, avoiding redundant unnecessary details. Use a dynamic and varied vocabulary for impact.\nComplementary Role: Use narration to complement dialogue and action, not overshadow them.\nAvoid Repetition: Ensure narration does not repeat information already conveyed through dialogue or action.\n\n### Narrative Consistency\nContinuity: Adhere to established story elements, expanding without contradicting previous details.\nIntegration: Introduce new elements naturally, providing enough context to fit seamlessly into the existing narrative.\n\n### Character Embodiment\nAnalysis: Examine the context, subtext, and implications of the given information to gain a deeper understandings of the characters'.\nReflection: Take time to consider the situation, characters' motivations, and potential consequences.\nAuthentic Portrayal: Bring characters to life by consistently and realistically portraying their unique traits, thoughts, emotions, appearances, physical sensations, speech patterns, and tone. Ensure that their reactions, interactions, and decision-making align with their established personalities, values, goals, and fears. Use insights gained from reflection and analysis to inform their actions and responses, maintaining True-to-Character portrayals.\n\n<!-- End of Role-playing Guidelines -->"
    },
    "preset": {
        "temp": 0.8,
        "temperature_last": true,
        "top_p": 1,
        "top_k": 0,
        "top_a": 0.3,
        "tfs": 0.75,
        "epsilon_cutoff": 0,
        "eta_cutoff": 0,
        "typical_p": 1,
        "min_p": 0,
        "rep_pen": 1,
        "rep_pen_range": 0,
        "rep_pen_decay": 0,
        "rep_pen_slope": 1,
        "no_repeat_ngram_size": 0,
        "penalty_alpha": 0,
        "num_beams": 1,
        "length_penalty": 1,
        "min_length": 0,
        "encoder_rep_pen": 1,
        "freq_pen": 0,
        "presence_pen": 0,
        "skew": 0,
        "do_sample": true,
        "early_stopping": false,
        "dynatemp": false,
        "min_temp": 0,
        "max_temp": 2,
        "dynatemp_exponent": 1,
        "smoothing_factor": 0,
        "smoothing_curve": 1,
        "dry_allowed_length": 3,
        "dry_multiplier": 0.8,
        "dry_base": 1.75,
        "dry_sequence_breakers": "[\"\\n\", \":\", \"\\\"\", \"*\"]",
        "dry_penalty_last_n": 1024,
        "add_bos_token": true,
        "ban_eos_token": false,
        "skip_special_tokens": false,
        "mirostat_mode": 0,
        "mirostat_tau": 5,
        "mirostat_eta": 0.1,
        "guidance_scale": 1,
        "negative_prompt": "",
        "grammar_string": "",
        "json_schema": {},
        "banned_tokens": "",
        "sampler_priority": [
            "repetition_penalty",
            "presence_penalty",
            "frequency_penalty",
            "dry",
            "temperature",
            "dynamic_temperature",
            "quadratic_sampling",
            "top_k",
            "top_p",
            "typical_p",
            "epsilon_cutoff",
            "eta_cutoff",
            "tfs",
            "top_a",
            "min_p",
            "mirostat",
            "xtc",
            "encoder_repetition_penalty",
            "no_repeat_ngram"
        ],
        "samplers": [
            "top_k",
            "tfs_z",
            "typical_p",
            "top_p",
            "min_p",
            "xtc",
            "temperature"
        ],
        "samplers_priorities": [
            "dry",
            "penalties",
            "no_repeat_ngram",
            "temperature",
            "top_nsigma",
            "top_p_top_k",
            "top_a",
            "min_p",
            "tfs",
            "eta_cutoff",
            "epsilon_cutoff",
            "typical_p",
            "quadratic",
            "xtc"
        ],
        "ignore_eos_token": false,
        "spaces_between_special_tokens": true,
        "speculative_ngram": false,
        "sampler_order": [
            6,
            0,
            1,
            3,
            4,
            2,
            5
        ],
        "logit_bias": [],
        "xtc_threshold": 0.1,
        "xtc_probability": 0,
        "nsigma": 0,
        "ignore_eos_token_aphrodite": false,
        "spaces_between_special_tokens_aphrodite": true,
        "rep_pen_size": 0,
        "genamt": 1024,
        "max_length": 16384,
        "name": "TQ-Aletheia"
    }
}