mirror of
https://github.com/xai-org/grok-1.git
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58 lines
2.1 KiB
Markdown
58 lines
2.1 KiB
Markdown
# Grok-1
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This repository contains JAX example code for loading and running the Grok-1 open-weights model.
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Make sure to download the checkpoint and place the `ckpt-0` directory in `checkpoints` - see [Downloading the weights](#downloading-the-weights)
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Then, run
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```shell
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pip install -r requirements.txt
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python run.py
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```
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to test the code.
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The script loads the checkpoint and samples from the model on a test input.
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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.
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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.
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# Model Specifications
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Grok-1 is currently designed with the following specifications:
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- **Parameters:** 314B
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- **Architecture:** Mixture of 8 Experts (MoE)
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- **Experts Utilization:** 2 experts used per token
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- **Layers:** 64
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- **Attention Heads:** 48 for queries, 8 for keys/values
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- **Embedding Size:** 6,144
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- **Tokenization:** SentencePiece tokenizer with 131,072 tokens
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- **Additional Features:**
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- Rotary embeddings (RoPE)
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- Supports activation sharding and 8-bit quantization
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- **Maximum Sequence Length (context):** 8,192 tokens
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# Downloading the weights
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You can download the weights using a torrent client and this magnet link:
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```
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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
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```
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318.GB ( Estimated disk size )
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or directly using [HuggingFace 🤗 Hub](https://huggingface.co/xai-org/grok-1):
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```
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git clone https://github.com/xai-org/grok-1.git && cd grok-1
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pip install huggingface_hub[hf_transfer]
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huggingface-cli download xai-org/grok-1 --repo-type model --include ckpt-0/* --local-dir checkpoints --local-dir-use-symlinks False
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```
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# License
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The code and associated Grok-1 weights in this release are licensed under the
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Apache 2.0 license. The license only applies to the source files in this
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repository and the model weights of Grok-1.
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