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Jason Liu
2023-11-06 17:02:46 -05:00
parent 0774efab90
commit 1d0cd798e9
3 changed files with 11 additions and 1 deletions
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examples/distilations/math_finetunes_val.jsonl
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{"messages": [{"role": "system", "content": "Predict the results of this function:\n\ndef fn(a: int, b: int, c: str) -> __main__.Multiply\n\"\"\"\n_summary_\n\nArgs:\n a (int): _description_\n b (int): _description_\n c (str): _description_\n\nReturns:\n Response: _description_\n\"\"\""}, {"role": "user", "content": "Return `fn(540, b=677, c=\"hello\")`"}, {"role": "assistant", "function_call": {"name": "Multiply", "arguments": "{\n \"a\": 540,\n \"b\": 677,\n \"result\": 1217\n}"}}], "functions": [{"name": "Multiply", "description": "Correctly extracted `Multiply` with all the required parameters with correct types", "parameters": {"properties": {"a": {"type": "integer"}, "b": {"type": "integer"}, "result": {"description": "The result of the multiplication", "type": "integer"}}, "required": ["a", "b", "result"], "type": "object"}}]}
{"messages": [{"role": "system", "content": "Predict the results of this function:\n\ndef fn(a: int, b: int, c: str) -> __main__.Multiply\n\"\"\"\n_summary_\n\nArgs:\n a (int): _description_\n b (int): _description_\n c (str): _description_\n\nReturns:\n Response: _description_\n\"\"\""}, {"role": "user", "content": "Return `fn(798, b=534, c=\"hello\")`"}, {"role": "assistant", "function_call": {"name": "Multiply", "arguments": "{\n \"a\": 798,\n \"b\": 534,\n \"result\": 1332\n}"}}], "functions": [{"name": "Multiply", "description": "Correctly extracted `Multiply` with all the required parameters with correct types", "parameters": {"properties": {"a": {"type": "integer"}, "b": {"type": "integer"}, "result": {"description": "The result of the multiplication", "type": "integer"}}, "required": ["a", "b", "result"], "type": "object"}}]}
{"messages": [{"role": "system", "content": "Predict the results of this function:\n\ndef fn(a: int, b: int, c: str) -> __main__.Multiply\n\"\"\"\n_summary_\n\nArgs:\n a (int): _description_\n b (int): _description_\n c (str): _description_\n\nReturns:\n Response: _description_\n\"\"\""}, {"role": "user", "content": "Return `fn(608, b=669, c=\"hello\")`"}, {"role": "assistant", "function_call": {"name": "Multiply", "arguments": "{\n \"a\": 608,\n \"b\": 669,\n \"result\": 1277\n}"}}], "functions": [{"name": "Multiply", "description": "Correctly extracted `Multiply` with all the required parameters with correct types", "parameters": {"properties": {"a": {"type": "integer"}, "b": {"type": "integer"}, "result": {"description": "The result of the multiplication", "type": "integer"}}, "required": ["a", "b", "result"], "type": "object"}}]}
{"messages": [{"role": "system", "content": "Predict the results of this function:\n\ndef fn(a: int, b: int, c: str) -> __main__.Multiply\n\"\"\"\n_summary_\n\nArgs:\n a (int): _description_\n b (int): _description_\n c (str): _description_\n\nReturns:\n Response: _description_\n\"\"\""}, {"role": "user", "content": "Return `fn(982, b=768, c=\"hello\")`"}, {"role": "assistant", "function_call": {"name": "Multiply", "arguments": "{\n \"a\": 982,\n \"b\": 768,\n \"result\": 1750\n}"}}], "functions": [{"name": "Multiply", "description": "Correctly extracted `Multiply` with all the required parameters with correct types", "parameters": {"properties": {"a": {"type": "integer"}, "b": {"type": "integer"}, "result": {"description": "The result of the multiplication", "type": "integer"}}, "required": ["a", "b", "result"], "type": "object"}}]}
examples/distilations/readme.md
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```
Wait for the fine-tuning job to complete.
If you have validation date you can run:
```
instructor jobs create-from-file math_finetunes.jsonl --n-epochs 4 --validation-file math_finetunes_val.jsonl
```
### Output
That's it! You've successfully run the script and can now proceed to fine-tune your model.
pyproject.toml
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[tool.poetry]
name = "instructor"
version = "0.2.9"
version = "0.2.11"
description = "Helper functions that allow us to improve openai's function_call ergonomics"
authors = ["Jason <jason@jxnl.co>"]
license = "MIT"