AMajor/grok-1
1
0
Fork 0
mirror of https://github.com/xai-org/grok-1.git synced 2024-11-24 12:39:54 +03:00
Code Issues Packages Projects Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
Kiruthik 2024-10-06 17:08:48 +05:30 committed by GitHub
parent 7050ed204b
commit 5f12cdd262
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 53 additions and 27 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

80
README.md
View File

@ -1,24 +1,39 @@
# Grok-1 # Grok-1
This repository contains JAX example code for loading and running the Grok-1 open-weights model. This repository contains JAX example code for loading and running the **Grok-1** open-weights model, developed by xAI, founded by Elon Musk. Grok-1 is designed to tackle a variety of natural language processing tasks effectively. This document will guide you through the setup, usage, and specifications of the model.
Make sure to download the checkpoint and place the `ckpt-0` directory in `checkpoints` - see [Downloading the weights](#downloading-the-weights) ## Table of Contents
Then, run - [Overview](#overview)
- [Getting Started](#getting-started)
- [Model Specifications](#model-specifications)
- [Downloading Weights](#downloading-weights)
- [Usage](#usage)
- [License](#license)
```shell ## Overview
pip install -r requirements.txt
python run.py
```
to test the code. Grok-1 is an advanced AI model characterized by its large parameter count and a unique architectural approach utilizing a Mixture of Experts (MoE) framework. This model not only serves as a powerful tool for NLP applications but also provides an exciting opportunity for developers and researchers to explore cutting-edge AI technologies.
The script loads the checkpoint and samples from the model on a test input. ## Getting Started
Due to the large size of the model (314B parameters), a machine with enough GPU memory is required to test the model with the example code. To set up and run Grok-1, follow these steps:
The implementation of the MoE layer in this repository is not efficient. The implementation was chosen to avoid the need for custom kernels to validate the correctness of the model.
# Model Specifications 1. **Clone the repository:**
```shell
git clone https://github.com/xai-org/grok-1.git
cd grok-1
```
2. **Install required dependencies:**
```shell
pip install -r requirements.txt
```
3. **Download the model weights:**
Ensure that you download the checkpoint and place the `ckpt-0` directory in `checkpoints` (see [Downloading Weights](#downloading-weights)).
## Model Specifications
Grok-1 is currently designed with the following specifications: Grok-1 is currently designed with the following specifications:
@ -29,28 +44,39 @@ Grok-1 is currently designed with the following specifications:
- **Attention Heads:** 48 for queries, 8 for keys/values - **Attention Heads:** 48 for queries, 8 for keys/values
- **Embedding Size:** 6,144 - **Embedding Size:** 6,144
- **Tokenization:** SentencePiece tokenizer with 131,072 tokens - **Tokenization:** SentencePiece tokenizer with 131,072 tokens
- **Maximum Sequence Length (context):** 8,192 tokens
- **Additional Features:** - **Additional Features:**
- Rotary embeddings (RoPE) - Rotary embeddings (RoPE)
- Supports activation sharding and 8-bit quantization - Supports activation sharding and 8-bit quantization
- **Maximum Sequence Length (context):** 8,192 tokens
# Downloading the weights ## Downloading Weights
You can download the weights using a torrent client and this magnet link: You can download the weights using two methods:
1. **Using a Torrent Client:**
Download the weights using the following magnet link:
```
magnet:?xt=urn:btih:5f96d43576e3d386c9ba65b883210a393b68210e&tr=https%3A%2F%2Facademictorrents.com%2Fannounce.php&tr=udp%3A%2F%2Ftracker.coppersurfer.tk%3A6969&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce
```
2. **Directly from Hugging Face Hub:**
Clone the repository and use the following commands:
```shell
git clone https://github.com/xai-org/grok-1.git && cd grok-1
pip install huggingface_hub[hf_transfer]
huggingface-cli download xai-org/grok-1 --repo-type model --include ckpt-0/* --local-dir checkpoints --local-dir-use-symlinks False
```
## Usage
To test the code, run the following command:
```shell
python run.py
``` ```
magnet:?xt=urn:btih:5f96d43576e3d386c9ba65b883210a393b68210e&tr=https%3A%2F%2Facademictorrents.com%2Fannounce.php&tr=udp%3A%2F%2Ftracker.coppersurfer.tk%3A6969&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce This script loads the checkpoint and samples from the model on a test input.
```
or directly using [HuggingFace 🤗 Hub](https://huggingface.co/xai-org/grok-1): **Note:** Due to the large size of the model (314B parameters), a machine with sufficient GPU memory is required to test the model with the example code. The current implementation of the MoE layer may not be fully optimized; it was chosen to facilitate correctness validation without the need for custom kernels.
```
git clone https://github.com/xai-org/grok-1.git && cd grok-1
pip install huggingface_hub[hf_transfer]
huggingface-cli download xai-org/grok-1 --repo-type model --include ckpt-0/* --local-dir checkpoints --local-dir-use-symlinks False
```
# License ## License
The code and associated Grok-1 weights in this release are licensed under the The code and associated Grok-1 weights in this release are licensed under the Apache 2.0 license. This license only applies to the source files in this repository and the model weights of Grok-1.
Apache 2.0 license. The license only applies to the source files in this
repository and the model weights of Grok-1.