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165 lines
5.0 KiB
Markdown
165 lines
5.0 KiB
Markdown
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### G4F - Local Usage Guide
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### Table of Contents
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1. [Introduction](#introduction)
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2. [Required Dependencies](#required-dependencies)
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3. [Basic Usage Example](#basic-usage-example)
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4. [Supported Models](#supported-models)
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5. [Performance Considerations](#performance-considerations)
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6. [Troubleshooting](#troubleshooting)
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#### Introduction
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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.
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## Usage
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#### Local inference
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How to use g4f to run language models locally
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#### Required dependencies
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**Make sure to install the required dependencies by running:**
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```bash
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pip install g4f[local]
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```
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or
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```bash
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pip install -U gpt4all
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```
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#### Basic usage example
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```python
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from g4f.local import LocalClient
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client = LocalClient()
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response = client.chat.completions.create(
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model = 'orca-mini-3b',
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messages = [{"role": "user", "content": "hi"}],
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stream = True
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)
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for token in response:
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print(token.choices[0].delta.content or "")
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```
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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.
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You can also manually place supported models into `./g4f/local/models/`
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**You can get a list of the current supported models by running:**
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```python
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from g4f.local import LocalClient
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client = LocalClient()
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client.list_models()
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```
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```json
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{
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"mistral-7b": {
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"path": "mistral-7b-openorca.gguf2.Q4_0.gguf",
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"ram": "8",
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"prompt": "<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n",
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"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|>"
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},
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"mistral-7b-instruct": {
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"path": "mistral-7b-instruct-v0.1.Q4_0.gguf",
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"ram": "8",
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"prompt": "[INST] %1 [/INST]",
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"system": None
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},
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"gpt4all-falcon": {
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"path": "gpt4all-falcon-newbpe-q4_0.gguf",
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"ram": "8",
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"prompt": "### Instruction:\n%1\n### Response:\n",
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"system": None
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},
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"orca-2": {
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"path": "orca-2-13b.Q4_0.gguf",
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"ram": "16",
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"prompt": None,
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"system": None
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},
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"wizardlm-13b": {
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"path": "wizardlm-13b-v1.2.Q4_0.gguf",
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"ram": "16",
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"prompt": None,
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"system": None
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},
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"nous-hermes-llama2": {
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"path": "nous-hermes-llama2-13b.Q4_0.gguf",
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"ram": "16",
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"prompt": "### Instruction:\n%1\n### Response:\n",
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"system": None
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},
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"gpt4all-13b-snoozy": {
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"path": "gpt4all-13b-snoozy-q4_0.gguf",
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"ram": "16",
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"prompt": None,
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"system": None
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},
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"mpt-7b-chat": {
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"path": "mpt-7b-chat-newbpe-q4_0.gguf",
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"ram": "8",
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"prompt": "<|im_start|>user\n%1<|im_end|>\n<|im_start|>assistant\n",
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"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|>"
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},
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"orca-mini-3b": {
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"path": "orca-mini-3b-gguf2-q4_0.gguf",
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"ram": "4",
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"prompt": "### User:\n%1\n### Response:\n",
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"system": "### System:\nYou are an AI assistant that follows instruction extremely well. Help as much as you can.\n\n"
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},
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"replit-code-3b": {
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"path": "replit-code-v1_5-3b-newbpe-q4_0.gguf",
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"ram": "4",
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"prompt": "%1",
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"system": None
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},
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"starcoder": {
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"path": "starcoder-newbpe-q4_0.gguf",
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"ram": "4",
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"prompt": "%1",
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"system": None
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},
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"rift-coder-7b": {
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"path": "rift-coder-v0-7b-q4_0.gguf",
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"ram": "8",
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"prompt": "%1",
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"system": None
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},
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"all-MiniLM-L6-v2": {
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"path": "all-MiniLM-L6-v2-f16.gguf",
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"ram": "1",
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"prompt": None,
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"system": None
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},
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"mistral-7b-german": {
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"path": "em_german_mistral_v01.Q4_0.gguf",
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"ram": "8",
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"prompt": "USER: %1 ASSISTANT: ",
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"system": "Du bist ein hilfreicher Assistent. "
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}
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}
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```
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#### Performance Considerations
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**When running language models locally, consider the following:**
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- RAM requirements vary by model size (see the 'ram' field in the model list).
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- CPU/GPU capabilities affect inference speed.
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- Disk space is needed to store the model files.
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#### Troubleshooting
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**Common issues and solutions:**
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1. **Model download fails**: Check your internet connection and try again.
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2. **Out of memory error**: Choose a smaller model or increase your system's RAM.
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3. **Slow inference**: Consider using a GPU or a more powerful CPU.
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[Return to Home](/)
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