Lynn: Llama 3 Soliloquy 8B v2

Description

Soliloquy-L3 v2 is a fast, highly capable roleplaying model designed for immersive, dynamic experiences. Trained on over 250 million tokens of roleplaying data, Soliloquy-L3 has a vast knowledge base, rich literary expression, and support for up to 24k context length. It outperforms existing ~13B models, delivering enhanced roleplaying capabilities.

Usage of this model is subject to Meta's Acceptable Use Policy.

Prompt

I need to take this json:

{
'first_name': 'Jane',
'last_name': 'Smith',
'date_of_birth': '03/16/1977',
orders: [
{
'created': '2024-01-25T15:00:04',
'amount': '100.00'
}
]}

And generate some dataclasses.

date_of_birth needs to be a date.
created is a datetime.
amount is a decimal.

How would I do this using the marshmallow library in python?

Inorder to create a response:

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (0.0) (0.52¢)

I apologize, but there is no actual solution provided in the text you've given me to evaluate. The text "Inorder to create a response:" is not a complete or meaningful solution to the problem described.

Without a solution to evaluate, I cannot assign any marks or provide a meaningful assessment. A proper solution would typically involve Python code that defines dataclasses, uses the marshmallow library to create schemas, and implements the required data type conversions.

Given the absence of a solution, the score breakdown would be:

{
  "marks 1": 0,
  "marks 2": 0,
  "marks 3": 0,
  "marks 4": 0,
  "marks 5": 0,
  "marks 6": 0
}

And the total score would be:

{
  "scores": [0, 0, 0, 0, 0, 0],
  "total_score": 0
}

If you have an actual solution to evaluate, please provide it, and I'd be happy to assess it based on the given marking scheme.

openai/gpt-4-0125-preview says: (0.0) ()

The provided response seems incomplete and does not include the actual solution for evaluating. It appears to be an introductory line without further content, thus providing no meaningful information or a solution to the problem statement. Below is a breakdown based on the expected criteria from the problem statement:

  1. Dataclasses for Person and Order: No dataclasses are defined in the given response.
  2. Schema Classes for Person and Order: No schema classes are defined either.
  3. Date Format for date_of_birth Field: There is no mention of field formatting or handling in the response.
  4. Decimal Field with as_string=True: This requirement is not addressed since there is no implementation provided.
  5. Linking Schema and Dataclasses with @post_load Method: The solution does not include any methods or marshmallow-specific code to evaluate.
  6. Any Additional Implementation or Correct Usage of Features: No features or additional code were provided to evaluate.

This response does not fulfill any of the requirements set in the marking scheme. Thus, a score based on the provided solution would be as follows:

{
  "score": 0
}

An interesting question!

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (0.0) (0.53¢)

I apologize, but the solution provided is not actually a solution to the problem. The text "An interesting question!" does not contain any code or implementation details that can be evaluated against the marking scheme.

Given this situation, I cannot award any marks as there is no implementation to assess. Here's the breakdown of marks and the total score:

{
  "marks 1": 0,
  "marks 2": 0,
  "marks 3": 0,
  "marks 4": 0,
  "marks 5": 0,
  "marks 6": 0
}
{
  "scores": [0, 0, 0, 0, 0, 0],
  "total_score": 0
}

Comment: The provided text does not constitute a solution to the problem. To receive marks, a proper implementation using the marshmallow library to create dataclasses and schemas for the given JSON structure would be required. The solution should include dataclass definitions, schema classes with appropriate field types and configurations, and the use of @post_load decorators to link schemas with dataclasses.

openai/gpt-4-0125-preview says: (0.0) ()

The provided "solution" does not include any actual content relevant to implementing dataclasses or marshmallow schemas in Python for the given JSON data. Therefore, without actual code to review in context to the described task or any steps towards solving the problem, it is impossible to appropriately assign a score based on the marking scheme provided.

Here's the breakdown based on the hypothetical fulfillment:
- Neither the necessary dataclasses nor their corresponding schema classes are defined. This ommission results in missing key constructs required for parsing and validating the JSON structure (0/4 marks).
- There's no specification in the solution for the format of the date_of_birth field, which should have been specified as "%m/%d/%Y" (0/1 mark).
- The solution doesn't address the need to handle the amount field as a decimal and specify serialization preferences such as as_string=True (0/1 mark).
- There is no mention of a @post_load method to link schema and dataclass objects, which is crucial for the correct instantiation of dataclass instances post deserialization (0/2 marks).
- No additional functionalities, explanations, or improvements are present in the response that could warrant awarding additional marks (0/2 marks).

The total score reflects a complete lack of response to the original question:

{
  "score": 0
}

Here is the answer to your questions:

date_of_birth needs to be said that that who taught me how to do this using the library. In this case just to do this to generate some dataclasses using Marsh or computation and python inoses used in above reply or descend. In this case,Ability, to be quickly nargs. In this case just,... to generate%) between dates. In this case analysis,... some dataclasses using.

                          In this case analysis.,... some dataclasses using.querySelectorAll.
  1. In this case analysis.,... some dataclasses using.] In this case.' In this case.

'' Some dataclasses using.] In this case., In some.dataclasses/.

In this怀 too In this case.] in some.data..

'. In this case.]

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (0.0) (0.72¢)

I'll evaluate this solution based on the provided marking scheme:

Evaluation:

The provided solution does not actually address the problem or implement any of the required components. It appears to be a collection of incomplete and unrelated sentences, possibly generated by an AI system that didn't understand the task. The solution doesn't contain any code or meaningful explanation related to using marshmallow to create dataclasses from the given JSON.

Breakdown of marks:

{
  "Define two dataclasses": 0,
  "Define two schema classes": 0,
  "Specify date format for date_of_birth": 0,
  "Use as_string=True for decimal field": 0,
  "Link schema and dataclasses with @post_load": 0,
  "Anything else": 0
}

The solution doesn't earn any marks as it fails to address any of the requirements specified in the marking scheme.

Score:

{
  "scores": [0, 0, 0, 0, 0, 0],
  "total_score": 0
}

Comment:
The provided solution is completely off-topic and does not attempt to solve the problem at hand. It doesn't use the marshmallow library, create any dataclasses, or handle the JSON data as requested. The text appears to be nonsensical and unrelated to the task. A proper solution would involve importing necessary libraries, defining dataclasses for Person and Order, creating corresponding marshmallow schemas, and implementing the required field types and decorators.

openai/gpt-4-0125-preview says: (0.0) ()

The provided solution does not meet the requirements outlined in the problem statement. Here is the breakdown based on the criteria provided in the marking scheme:

  1. Two dataclasses for person and order: The solution does not define dataclasses for a person or for an order. It does not even mention the use of dataclasses from Python's dataclasses module. (0 marks)
  2. Two schema classes for person and order: The solution also fails to define schema classes using Marshmallow or any other relevant descriptions that match the needs specified. (0 marks)
  3. Specify the date format for date_of_ birth: There is no mention of handling or formatting the date_of_birth field as specified in the problem statement. (0 marks)
  4. Decimal field need as_string=True: Again, the solution does not address converting amount to a decimal, nor does it specify serializer settings such as as_string=True. (0 marks)
  5. Linking schema and dataclasses with @post_load method: The solution does not implement or mention the @post_load decorator or methods to perform the transformation from Marshmallow schema to Python dataclasses. (0 marks)
  6. Additional considerations (clarity, completeness, etc.): The solution provided is incoherent, lacks any programmatic response, relevant examples, or understandable description related to the problem. (0 marks)

Overall the response does not address any part of the task correctly and provides no usable information or implementation according to the initial requirements.

Final score:

{
  "score": 0
}