### G4F - Local Usage Guide ### Table of Contents 1. [Introduction](#introduction) 2. [Required Dependencies](#required-dependencies) 3. [Basic Usage Example](#basic-usage-example) 4. [Supported Models](#supported-models) 5. [Performance Considerations](#performance-considerations) 6. [Troubleshooting](#troubleshooting) #### Introduction This guide explains how to use g4f to run language models locally. G4F (GPT4Free) allows you to interact with various language models on your local machine, providing a flexible and private solution for natural language processing tasks. ## Usage #### Local inference How to use g4f to run language models locally #### Required dependencies **Make sure to install the required dependencies by running:** ```bash pip install g4f[local] ``` or ```bash pip install -U gpt4all ``` #### Basic usage example ```python from g4f.local import LocalClient client = LocalClient() response = client.chat.completions.create( model = 'orca-mini-3b', messages = [{"role": "user", "content": "hi"}], stream = True ) for token in response: print(token.choices[0].delta.content or "") ``` Upon first use, there will be a prompt asking you if you wish to download the model. If you respond with `y`, g4f will go ahead and download the model for you. You can also manually place supported models into `./g4f/local/models/` **You can get a list of the current supported models by running:** ```python from g4f.local import LocalClient client = LocalClient() client.list_models() ``` ```json { "mistral-7b": { "path": "mistral-7b-openorca.gguf2.Q4_0.gguf", "ram": "8", "prompt": "<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n", "system": "<|im_start|>system\nYou are MistralOrca, a large language model trained by Alignment Lab AI. For multi-step problems, write out your reasoning for each step.\n<|im_end|>" }, "mistral-7b-instruct": { "path": "mistral-7b-instruct-v0.1.Q4_0.gguf", "ram": "8", "prompt": "[INST] %1 [/INST]", "system": None }, "gpt4all-falcon": { "path": "gpt4all-falcon-newbpe-q4_0.gguf", "ram": "8", "prompt": "### Instruction:\n%1\n### Response:\n", "system": None }, "orca-2": { "path": "orca-2-13b.Q4_0.gguf", "ram": "16", "prompt": None, "system": None }, "wizardlm-13b": { "path": "wizardlm-13b-v1.2.Q4_0.gguf", "ram": "16", "prompt": None, "system": None }, "nous-hermes-llama2": { "path": "nous-hermes-llama2-13b.Q4_0.gguf", "ram": "16", "prompt": "### Instruction:\n%1\n### Response:\n", "system": None }, "gpt4all-13b-snoozy": { "path": "gpt4all-13b-snoozy-q4_0.gguf", "ram": "16", "prompt": None, "system": None }, "mpt-7b-chat": { "path": "mpt-7b-chat-newbpe-q4_0.gguf", "ram": "8", "prompt": "<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n", "system": "<|im_start|>system\n- You are a helpful assistant chatbot trained by MosaicML.\n- You answer questions.\n- You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.\n- You are more than just an information source, you are also able to write poetry, short stories, and make jokes.<|im_end|>" }, "orca-mini-3b": { "path": "orca-mini-3b-gguf2-q4_0.gguf", "ram": "4", "prompt": "### User:\n%1\n### Response:\n", "system": "### System:\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\n" }, "replit-code-3b": { "path": "replit-code-v1_5-3b-newbpe-q4_0.gguf", "ram": "4", "prompt": "%1", "system": None }, "starcoder": { "path": "starcoder-newbpe-q4_0.gguf", "ram": "4", "prompt": "%1", "system": None }, "rift-coder-7b": { "path": "rift-coder-v0-7b-q4_0.gguf", "ram": "8", "prompt": "%1", "system": None }, "all-MiniLM-L6-v2": { "path": "all-MiniLM-L6-v2-f16.gguf", "ram": "1", "prompt": None, "system": None }, "mistral-7b-german": { "path": "em_german_mistral_v01.Q4_0.gguf", "ram": "8", "prompt": "USER: %1 ASSISTANT: ", "system": "Du bist ein hilfreicher Assistent. " } } ``` #### Performance Considerations **When running language models locally, consider the following:** - RAM requirements vary by model size (see the 'ram' field in the model list). - CPU/GPU capabilities affect inference speed. - Disk space is needed to store the model files. #### Troubleshooting **Common issues and solutions:** 1. **Model download fails**: Check your internet connection and try again. 2. **Out of memory error**: Choose a smaller model or increase your system's RAM. 3. **Slow inference**: Consider using a GPU or a more powerful CPU. [Return to Home](/)