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Updates to notebook; use direct requests to NeMo where needed
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parent
c04ab0133d
commit
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6 changed files with 659 additions and 155 deletions
34
docs/_static/llama-stack-spec.html
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34
docs/_static/llama-stack-spec.html
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@ -6347,7 +6347,36 @@
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"default": "model"
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},
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"model": {
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"type": "string",
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"oneOf": [
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{
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"type": "string"
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},
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{
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"type": "object",
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"additionalProperties": {
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"oneOf": [
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{
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"type": "null"
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},
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{
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"type": "boolean"
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},
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{
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"type": "number"
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},
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{
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"type": "string"
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},
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{
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"type": "array"
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},
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{
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"type": "object"
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}
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]
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}
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}
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],
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"description": "The model ID to evaluate."
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},
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"sampling_params": {
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@ -6362,8 +6391,7 @@
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"additionalProperties": false,
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"required": [
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"type",
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"model",
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"sampling_params"
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"model"
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],
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"title": "ModelCandidate",
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"description": "A model candidate for evaluation."
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13
docs/_static/llama-stack-spec.yaml
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13
docs/_static/llama-stack-spec.yaml
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@ -4468,7 +4468,17 @@ components:
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const: model
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default: model
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model:
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type: string
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oneOf:
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- type: string
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- type: object
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additionalProperties:
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oneOf:
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- type: 'null'
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- type: boolean
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- type: number
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- type: string
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- type: array
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- type: object
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description: The model ID to evaluate.
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sampling_params:
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$ref: '#/components/schemas/SamplingParams'
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@ -4482,7 +4492,6 @@ components:
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required:
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- type
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- model
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- sampling_params
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title: ModelCandidate
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description: A model candidate for evaluation.
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RegexParserScoringFnParams:
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File diff suppressed because it is too large
Load diff
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@ -27,8 +27,8 @@ class ModelCandidate(BaseModel):
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"""
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type: Literal["model"] = "model"
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model: str
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sampling_params: SamplingParams
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model: Union[str, Dict[str, Any]]
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sampling_params: Optional[SamplingParams] = Field(default_factory=SamplingParams)
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system_message: Optional[SystemMessage] = None
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@ -48,13 +48,13 @@ class NVIDIAEvalImpl(
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async def _evaluator_get(self, path):
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"""Helper for making GET requests to the evaluator service."""
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response = requests.get(url=f"{self.config.evaluator_service_url}/{path}")
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response = requests.get(url=f"{self.config.evaluator_service_url}{path}")
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response.raise_for_status()
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return response.json()
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async def _evaluator_post(self, path, data):
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"""Helper for making POST requests to the evaluator service."""
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response = requests.post(url=f"{self.config.evaluator_service_url}/{path}", json=data)
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response = requests.post(url=f"{self.config.evaluator_service_url}{path}", json=data)
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response.raise_for_status()
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return response.json()
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@ -408,7 +408,7 @@ class NvidiaPostTrainingAdapter(ModelRegistryHelper):
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if v is not None
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}
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else:
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raise NotImplementedError(f"JASH was here Unsupported algorithm config: {algorithm_config}")
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raise NotImplementedError(f"Unsupported algorithm config: {algorithm_config}")
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# Create the customization job
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response = await self._make_request(
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