zgene
6bed393c12
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126 lines
2.9 KiB
JSON
126 lines
2.9 KiB
JSON
[
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{
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"name": "temperature",
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"label": "回复随机性",
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"desc": "即 Temperature，较高的 Temperature 会让模型生成更多样和创新的文本，反之生成内容会更加保守且类似于训练数据。",
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"type": 1,
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"min": "0",
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"max": "2",
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"precision": 2,
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"default_val": {
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"default_val": "1",
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"creative": "0.8",
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"balance": "0.5",
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"precise": "0.1"
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},
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"options": [],
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"param_class": {
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"class_id": 1,
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"label": "生成多样性"
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}
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},
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{
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"name": "top_p",
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"label": "Top P",
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"desc": "设定Top p概率阈值，模型在生成文本时只从概率超过阈值的词汇中选择，从而控制文本的多样性",
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"type": 1,
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"min": "0",
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"max": "1",
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"precision": 2,
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"default_val": {
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"default_val": "1",
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"creative": "1",
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"balance": "1",
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"precise": "1"
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},
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"options": [],
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"param_class": {
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"class_id": 1,
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"label": "生成多样性"
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}
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},
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{
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"name": "frequency_penalty",
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"label": "重复词汇惩罚",
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"desc": "当该值为正时，它会降低已出现词汇的重复率，进而提高模型输出词汇的多样性",
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"type": 1,
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"min": "-2",
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"max": "2",
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"precision": 2,
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"default_val": {
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"default_val": "0",
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"creative": "0",
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"balance": "0",
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"precise": "0"
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},
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"options": [],
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"param_class": {
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"class_id": 1,
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"label": "生成多样性"
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}
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},
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{
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"name": "presence_penalty",
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"label": "存在惩罚",
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"desc": "减少已提及内容的重复，增加新主题和概念的引入，促进内容的多元化。",
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"type": 1,
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"min": "-2",
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"max": "2",
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"precision": 2,
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"default_val": {
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"default_val": "0",
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"creative": "0",
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"balance": "0",
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"precise": "0"
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},
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"options": [],
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"param_class": {
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"class_id": 1,
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"label": "生成多样性"
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}
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},
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{
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"name": "max_tokens",
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"label": "最大回复长度",
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"desc": "可控制模型回复的最多 Token 数量，以满足不同场景和需求。通常 100 Tokens 约等于 60 个中文汉字。",
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"type": 2,
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"min": "1",
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"max": "16384",
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"precision": 0,
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"default_val": {
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"default_val": "2048"
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},
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"options": [],
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"param_class": {
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"class_id": 2,
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"label": "输入及输出长度"
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}
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},
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{
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"name": "response_format",
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"label": "输出格式",
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"desc": "文本: 使用普通文本格式回复Markdown: 将强制模型使用Markdown格式输出回复\nJSON: 将强制模型使用 JSON 格式输出回复",
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"type": 2,
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"min": "",
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"max": "",
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"precision": 0,
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"default_val": {
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"default_val": "0"
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},
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"options": [
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{
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"label": "文本",
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"value": "0"
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},
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{
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"label": "Markdown",
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"value": "1"
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}
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],
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"param_class": {
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"class_id": 2,
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"label": "输入及输出长度"
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}
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}
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]
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