Instructions to use itsanan/codebert-finetuned-crewai-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use itsanan/codebert-finetuned-crewai-base with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("itsanan/codebert-finetuned-crewai-base")

sentences = [
    "How to implement __del__?",
    "class SampleMultiCrewFlow(Flow[SimpleState]):\n        @start()\n        def first_crew(self):\n            \"\"\"Run first crew.\"\"\"\n            agent = Agent(\n                role=\"first agent\",\n                goal=\"first task\",\n                backstory=\"first agent\",\n                llm=mock_llm_1,\n            )\n            task = Task(\n                description=\"First task\",\n                expected_output=\"first result\",\n                agent=agent,\n            )\n            crew = Crew(\n                agents=[agent],\n                tasks=[task],\n                share_crew=True,\n            )\n\n            result = crew.kickoff()\n\n            assert crew._execution_span is not None\n            return str(result.raw)\n\n        @listen(first_crew)\n        def second_crew(self, first_result: str):\n            \"\"\"Run second crew.\"\"\"\n            agent = Agent(\n                role=\"second agent\",\n                goal=\"second task\",\n                backstory=\"second agent\",\n                llm=mock_llm_2,\n            )\n            task = Task(\n                description=\"Second task\",\n                expected_output=\"second result\",\n                agent=agent,\n            )\n            crew = Crew(\n                agents=[agent],\n                tasks=[task],\n                share_crew=True,\n            )\n\n            result = crew.kickoff()\n\n            assert crew._execution_span is not None\n\n            self.state.result = f\"{first_result} + {result.raw}\"\n            return self.state.result",
    "async def test_anthropic_async_with_tools():\n    \"\"\"Test async call with tools.\"\"\"\n    llm = AnthropicCompletion(model=\"claude-sonnet-4-0\")\n\n    tools = [\n        {\n            \"type\": \"function\",\n            \"function\": {\n                \"name\": \"get_weather\",\n                \"description\": \"Get the current weather for a location\",\n                \"parameters\": {\n                    \"type\": \"object\",\n                    \"properties\": {\n                        \"location\": {\n                            \"type\": \"string\",\n                            \"description\": \"The city and state, e.g. San Francisco, CA\"\n                        }\n                    },\n                    \"required\": [\"location\"]\n                }\n            }\n        }\n    ]\n\n    result = await llm.acall(\n        \"What's the weather in San Francisco?\",\n        tools=tools\n    )\n    logging.debug(\"result: %s\", result)\n\n    assert result is not None\n    assert isinstance(result, str)",
    "def __del__(self):\n        \"\"\"Cleanup connections on deletion.\"\"\"\n        try:\n            if self._connection_pool:\n                for conn in self._connection_pool:\n                    try:\n                        conn.close()\n                    except Exception:  # noqa: PERF203, S110\n                        pass\n            if self._thread_pool:\n                self._thread_pool.shutdown()\n        except Exception:  # noqa: S110\n            pass"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle

codebert-finetuned-crewai-base / .gitattributes

itsanan

initial commit

68e2da0 verified 4 months ago

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