GET
/v1/schemas/nvidia/chat/bigcode/starcoder2-15b
Accept:
| field | recorded source |
|---|---|
| schema | Source linked above. upstream-spec Source traceec4a8c3409e8d3792e72794af90ae93a87c3b865382761166edff399ab208f72{
"fetchedAt": 1791535404,
"extractorVersion": "1",
"verifiedAt": null
} |
Request body
9 properties · 0 required · 0 $defs| property | type | description | constraints |
|---|---|---|---|
| model | string | Name of target model. | default: "bigcode/starcoder2-15b" |
| prompt | string | string[] | User prompt. | length ≥ 1 · default: "# Python function that finds pr… |
| max_tokens | integer | Maximum number of tokens to generate. | 1 ≤ n ≤ 1024 · nullable |
| temperature | number | Control randomness by applying a scaling to the logits; a higher value has increased variety and a lower values makes sampling less diverse. | 0 ≤ n ≤ 2 · nullable |
| top_p | number | Also know as nucleus sampling - the cumulative probability cutoff for token selection. Using a lower value means sampling from a smaller set of candidates. This is done by sorting the logprobs and collecting them one by one until their cumulative sum exceed the top_p score. | 0 ≤ n ≤ 1 · nullable |
| stop | string | string[] | Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. | nullable |
| frequency_penalty | number | Indicates how much to penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. https://platform.openai.com/docs/api-reference/completions/create for details. Higher values increase the penalty. | -2 ≤ n ≤ 2 · nullable |
| presence_penalty | number | Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. | -2 ≤ n ≤ 2 · nullable |
| seed | integer | The model generates random results. Changing the input seed alone will produce a different response with similar characteristics. It is possible to reproduce results by fixing the input seed (assuming all other hyperparameters are also fixed). | 0 ≤ n ≤ 18446744073709552000 · nullable |
Validate a payload
before you spend tokensshell
$ curl -X POST https://modelschemas.com/v1/validate \
-d '{"provider":"nvidia","endpointId":"bigcode/starcoder2-15b","payload":{…}}'
→ {"valid": false, "errors": [{"path": "#", "keyword": "required", …}]}