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Model: allura-org/TQ2.5-14B-Aletheia-v1 Source: Original Platform
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TQ-Aletheia.json
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160
TQ-Aletheia.json
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{
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"instruct": {
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"wrap": false,
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"system_sequence": "<|im_start|>system\n",
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"stop_sequence": "<|im_end|>",
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"input_sequence": "<|im_start|>user\n",
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"output_sequence": "<|im_start|>assistant\n",
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"macro": true,
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"system_sequence_prefix": "",
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"system_sequence_suffix": "",
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"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",
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"last_output_sequence": "",
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"activation_regex": "",
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"skip_examples": true,
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"output_suffix": "<|im_end|>\n",
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"input_suffix": "<|im_end|>\n",
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"system_suffix": "<|im_end|>\n",
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"user_alignment_message": "",
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"last_system_sequence": "",
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"system_same_as_user": false,
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"first_input_sequence": "",
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"last_input_sequence": "",
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"names_behavior": "none",
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"names_force_groups": true,
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"name": "[ChatML]Roleplay-v1.9"
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},
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"context": {
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"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|>",
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"example_separator": "",
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"chat_start": "",
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"use_stop_strings": false,
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"allow_jailbreak": false,
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"names_as_stop_strings": true,
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"always_force_name2": true,
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"trim_sentences": false,
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"single_line": false,
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"name": "[ChatML] Roleplay-v1.9"
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},
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"sysprompt": {
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"name": "[Migrated] [ChatML]Roleplay-v1.9",
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"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 -->"
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},
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"preset": {
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"temp": 0.8,
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"temperature_last": true,
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"top_p": 1,
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"top_k": 0,
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"top_a": 0.3,
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"tfs": 0.75,
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"epsilon_cutoff": 0,
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"eta_cutoff": 0,
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"typical_p": 1,
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"min_p": 0,
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"rep_pen": 1,
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"rep_pen_range": 0,
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"rep_pen_decay": 0,
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"rep_pen_slope": 1,
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"no_repeat_ngram_size": 0,
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"penalty_alpha": 0,
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"num_beams": 1,
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"length_penalty": 1,
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"min_length": 0,
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"encoder_rep_pen": 1,
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"freq_pen": 0,
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"presence_pen": 0,
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"skew": 0,
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"do_sample": true,
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"early_stopping": false,
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"dynatemp": false,
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"min_temp": 0,
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"max_temp": 2,
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"dynatemp_exponent": 1,
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"smoothing_factor": 0,
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"smoothing_curve": 1,
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"dry_allowed_length": 3,
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"dry_multiplier": 0.8,
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"dry_base": 1.75,
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"dry_sequence_breakers": "[\"\\n\", \":\", \"\\\"\", \"*\"]",
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"dry_penalty_last_n": 1024,
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"add_bos_token": true,
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"ban_eos_token": false,
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"skip_special_tokens": false,
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"mirostat_mode": 0,
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"mirostat_tau": 5,
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"mirostat_eta": 0.1,
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"guidance_scale": 1,
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"negative_prompt": "",
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"grammar_string": "",
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"json_schema": {},
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"banned_tokens": "",
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"sampler_priority": [
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"repetition_penalty",
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"presence_penalty",
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"frequency_penalty",
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"dry",
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"temperature",
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"dynamic_temperature",
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"quadratic_sampling",
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"top_k",
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"top_p",
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"typical_p",
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"epsilon_cutoff",
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"eta_cutoff",
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"tfs",
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"top_a",
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"min_p",
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"mirostat",
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"xtc",
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"encoder_repetition_penalty",
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"no_repeat_ngram"
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],
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"samplers": [
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"top_k",
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"tfs_z",
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"typical_p",
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"top_p",
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"min_p",
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"xtc",
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"temperature"
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],
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"samplers_priorities": [
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"dry",
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"penalties",
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"no_repeat_ngram",
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"temperature",
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"top_nsigma",
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"top_p_top_k",
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"top_a",
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"min_p",
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"tfs",
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"eta_cutoff",
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"epsilon_cutoff",
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"typical_p",
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"quadratic",
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"xtc"
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],
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"ignore_eos_token": false,
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"spaces_between_special_tokens": true,
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"speculative_ngram": false,
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"sampler_order": [
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6,
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0,
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1,
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3,
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4,
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2,
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5
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],
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"logit_bias": [],
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"xtc_threshold": 0.1,
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"xtc_probability": 0,
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"nsigma": 0,
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"ignore_eos_token_aphrodite": false,
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"spaces_between_special_tokens_aphrodite": true,
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"rep_pen_size": 0,
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"genamt": 1024,
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"max_length": 16384,
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"name": "TQ-Aletheia"
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}
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}
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