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[WIP][documentation + parameters+states + optimizer] #22

Merged
merged 26 commits into from
May 31, 2024
Merged

[WIP][documentation + parameters+states + optimizer] #22

merged 26 commits into from
May 31, 2024

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liyin2015
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@liyin2015 liyin2015 commented May 20, 2024

  • the intro page for the library
  • the structure of all documentations
  • Yaml output format
Screen Shot 2024-05-21 at 12 13 49 AM Screen Shot 2024-05-21 at 12 25 37 AM Screen Shot 2024-05-21 at 12 18 13 AM
  • dataclass to support different formats and communicate with generator's prompt template
  • created our own few-shot bootstrap optimizer that has different sampling and optimizing method (random sample and class-balanced sampling for classification tasks)
  • added parameters, states_dict, save and load both json and pickle.
  • history tracking of parameters(save the states when each eval run)

- Do not output the class_name.
"""

EXAMPLES_STR = r"""Question: {{input}}
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input data class and output data class can form examples_str


def call(self, query: str) -> str:
str_response: Dict[str, Any] = self.generator.call(
input=query, prompt_kwargs={"input": query}
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the way to run llm it needs to take any number of input arguments -> and be passed to the generator! Need to design and think better.

@liyin2015 liyin2015 changed the title [WIP][documentation + polishing] [WIP][documentation + parameters+states + optimizer] May 25, 2024
@@ -0,0 +1,35 @@
from typing import Dict, Sequence
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duplicate file

liyin2015 added 2 commits May 26, 2024 00:15
…ss balanced sampling, achieve almost best performance with only 4 steps and each step is only batch size 5, cost 20 more times inference
self,
dataset,
num_classes: int,
get_data_key_fun: Callable,
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label_map_fun

@Sylph-AI Sylph-AI merged commit a74a1ac into main May 31, 2024
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2 participants