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model: us.anthropic.claude-3-5-haiku-20241022-v1:0 |
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label: |
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en_US: Claude 3.5 Haiku(US.Cross Region Inference) |
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model_type: llm |
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features: |
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- agent-thought |
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- vision |
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- tool-call |
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- stream-tool-call |
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model_properties: |
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mode: chat |
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context_size: 200000 |
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# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html |
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parameter_rules: |
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- name: max_tokens |
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use_template: max_tokens |
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required: true |
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type: int |
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default: 4096 |
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min: 1 |
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max: 4096 |
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help: |
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zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 |
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en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. |
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# docs: https://docs.anthropic.com/claude/docs/system-prompts |
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- name: temperature |
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use_template: temperature |
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required: false |
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type: float |
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default: 1 |
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min: 0.0 |
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max: 1.0 |
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help: |
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zh_Hans: 生成内容的随机性。 |
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en_US: The amount of randomness injected into the response. |
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- name: top_p |
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required: false |
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type: float |
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default: 0.999 |
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min: 0.000 |
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max: 1.000 |
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help: |
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zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。 |
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en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. |
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- name: top_k |
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required: false |
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type: int |
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default: 0 |
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min: 0 |
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# tip docs from aws has error, max value is 500 |
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max: 500 |
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help: |
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zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 |
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en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. |
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- name: response_format |
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use_template: response_format |
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pricing: |
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input: '0.001' |
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output: '0.005' |
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unit: '0.001' |
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currency: USD |