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 This repository contains JAX example code for loading and running the Grok-1 open-weights model.
 
-Make sure to download the checkpoint and place the `ckpt-0` directory in `checkpoints` - see [Downloading the weights](#downloading-the-weights)
-
-Then, run
-
-```shell
-pip install -r requirements.txt
-python run.py
-```
-
-to test the code.
-
-The script loads the checkpoint and samples from the model on a test input.
-
-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.
-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
-
-Grok-1 is currently designed with the following specifications:
-
-- **Parameters:** 314B
-- **Architecture:** Mixture of 8 Experts (MoE)
-- **Experts Utilization:** 2 experts used per token
-- **Layers:** 64
-- **Attention Heads:** 48 for queries, 8 for keys/values
-- **Embedding Size:** 6,144
-- **Tokenization:** SentencePiece tokenizer with 131,072 tokens
-- **Additional Features:**
-  - Rotary embeddings (RoPE)
-  - Supports activation sharding and 8-bit quantization
+zation
 - **Maximum Sequence Length (context):** 8,192 tokens
 
 # Downloading the weights