diff --git a/README.md b/README.md index 9e1d634..9d34cc7 100644 --- a/README.md +++ b/README.md @@ -18,19 +18,20 @@ GPT-J 6B is a transformer model trained using Ben Wang's [Mesh Transformer JAX](
-| Hyperparameter | Value | -|----------------------|---------------| -| \\(n_{parameters}\\) | 6,053,381,344 | -| \\(n_{layers}\\) | 28* | -| \\(d_{model}\\) | 4,096 | -| \\(d_{ff}\\) | 16,384 | -| \\(n_{heads}\\) | 16 | -| \\(d_{head}\\) | 256 | -| \\(n_{ctx}\\) | 2,048 | -| \\(n_{vocab}\\) | 50,257 (same tokenizer as GPT-2/3) | +| Hyperparameter | Value | +|----------------------|------------| +| \\(n_{parameters}\\) | 6053381344 | +| \\(n_{layers}\\) | 28* | +| \\(d_{model}\\) | 4096 | +| \\(d_{ff}\\) | 16384 | +| \\(n_{heads}\\) | 16 | +| \\(d_{head}\\) | 256 | +| \\(n_{ctx}\\) | 2048 | +| \\(n_{vocab}\\) | 50257/50400† (same tokenizer as GPT-2/3) | | Positional Encoding | [Rotary Position Embedding (RoPE)](https://arxiv.org/abs/2104.09864) | | RoPE Dimensions | [64](https://github.com/kingoflolz/mesh-transformer-jax/blob/f2aa66e0925de6593dcbb70e72399b97b4130482/mesh_transformer/layers.py#L223) | -
* Each layer consists of one feedforward block and one self attention block.
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* Each layer consists of one feedforward block and one self attention block.

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Although the embedding matrix has a size of 50400, only 50257 entries are used by the GPT-2 tokenizer.

The model consists of 28 layers with a model dimension of 4096, and a feedforward dimension of 16384. The model dimension is split into 16 heads, each with a dimension of 256. Rotary Position Embedding (RoPE) is applied to 64