text: It is broken into two parts: installation and setup, and then references to specific C Transformers wrappers.Installation and Setupâ€‹Install the Python package with pip install ctransformersDownload a supported GGML model (see Supported Models)Wrappersâ€‹LLMâ€‹There exists a CTransformers LLM wrapper, which you can access with:from langchain.llms import CTransformersIt provides a unified interface for all models:llm = CTransformers(model='/path/to/ggml-gpt-2.bin', model_type='gpt2')print(llm('AI is going to'))If you are getting illegal instruction error, try using lib='avx' or lib='basic':llm = CTransformers(model='/path/to/ggml-gpt-2.bin', model_type='gpt2', lib='avx')It can be used with models hosted on the Hugging Face Hub:llm = CTransformers(model='marella/gpt-2-ggml')If a model repo has multiple model files (.bin files), specify a model file using:llm = CTransformers(model='marella/gpt-2-ggml', model_file='ggml-model.bin')Additional parameters can be passed using the config parameter:config = {'max_new_tokens': 256, 'repetition_penalty': 1.1}llm = CTransformers(model='marella/gpt-2-ggml', config=config)See Documentation for a list of available parameters.For a more detailed walkthrough of this, see this notebook.PreviousConfluenceNextDatabricksInstallation and SetupWrappersLLMCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.