server-inference push mfrc
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36
config.json
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36
config.json
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{
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"model": null,
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"signature": {
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"description": "Classify the text into one or more MFRC-style moral foundation labels. As you reason, note any uncertainties, ambiguities, and gaps \u2014 both in how the instructions apply to the task at hand and in whether you have the knowledge needed to solve it. Be honest in your reasoning when you are unsure about your answer. Be honest in you reasoniing when you are unsure about your answer.",
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"properties": {
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"text": {
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"__dspy_field_type": "input",
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"desc": "The text to analyze for moral foundations.",
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"prefix": "Text:",
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"title": "Text",
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"type": "string"
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},
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"reasoning": {
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"__dspy_field_type": "output",
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"desc": "Step-by-step reasoning, including uncertainty, ambiguity, or uncertainty in your thought process when relevant.",
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"prefix": "Reasoning:",
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"title": "Reasoning",
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"type": "string"
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},
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"annotation": {
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"__dspy_field_type": "output",
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"desc": "Comma-separated moral foundation labels such as care, fairness, loyalty, authority, or non_moral.",
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"prefix": "Annotation:",
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"title": "Annotation",
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"type": "string"
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}
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},
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"required": [
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"text",
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"reasoning",
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"annotation"
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],
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"title": "MoralAnnotationJudgeSig",
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"type": "object"
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}
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}
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40
program.json
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40
program.json
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{
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"traces": [],
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"train": [],
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"demos": [],
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"signature": {
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"instructions": "Classify the text into one or more MFRC-style moral foundation labels. As you reason, note any uncertainties, ambiguities, and gaps \u2014 both in how the instructions apply to the task at hand and in whether you have the knowledge needed to solve it. Be honest in your reasoning when you are unsure about your answer. Be honest in you reasoniing when you are unsure about your answer.",
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"fields": [
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{
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"prefix": "Text:",
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"description": "The text to analyze for moral foundations."
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},
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{
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"prefix": "Reasoning:",
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"description": "Step-by-step reasoning, including uncertainty, ambiguity, or uncertainty in your thought process when relevant."
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},
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{
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"prefix": "Annotation:",
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"description": "Comma-separated moral foundation labels such as care, fairness, loyalty, authority, or non_moral."
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}
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]
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},
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"lm": {
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"model": "together_ai/Qwen/Qwen2.5-7B-Instruct-Turbo",
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"model_type": "chat",
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"cache": true,
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"num_retries": 3,
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"finetuning_model": null,
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"launch_kwargs": {},
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"train_kwargs": {},
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"temperature": null,
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"max_tokens": null
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},
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"metadata": {
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"dependency_versions": {
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"python": "3.11",
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"dspy": "3.1.3",
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"cloudpickle": "3.1"
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}
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}
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}
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