* 2023/03/20 Update the model weight and config files such that it can be loaded via Huggingface's official GPT-NeoX implementation.
Browse files- README.md +5 -7
- config.json +11 -29
- pytorch_model.bin +2 -2
README.md
CHANGED
@@ -22,17 +22,15 @@ inference: false
|
|
22 |
|
23 |
This repository provides a small-sized Japanese GPT-NeoX model. The model was trained using code based on [EleutherAI/gpt-neox](https://github.com/EleutherAI/gpt-neox).
|
24 |
|
25 |
-
#
|
|
|
26 |
|
27 |
-
|
28 |
-
* Use `T5Tokenizer` to load its corresponding tokenizer.
|
29 |
-
* The files for modeling and configuration are not in the Transformers library yet. In order to load the model, use files from [this PR in EleutherAI/gpt-neox](https://github.com/EleutherAI/gpt-neox/pull/480).
|
30 |
|
31 |
~~~~
|
32 |
-
from transformers import
|
33 |
-
from modeling_gpt_neox import GPTNeoXForCausalLM
|
34 |
|
35 |
-
tokenizer =
|
36 |
model = GPTNeoXForCausalLM.from_pretrained("rinna/japanese-gpt-neox-small")
|
37 |
~~~~
|
38 |
|
|
|
22 |
|
23 |
This repository provides a small-sized Japanese GPT-NeoX model. The model was trained using code based on [EleutherAI/gpt-neox](https://github.com/EleutherAI/gpt-neox).
|
24 |
|
25 |
+
# Update log
|
26 |
+
* 2023/03/20 Update the model weight and config files such that it can be loaded via Huggingface's official GPT-NeoX implementation.
|
27 |
|
28 |
+
# How to use the model
|
|
|
|
|
29 |
|
30 |
~~~~
|
31 |
+
from transformers import AutoTokenizer, AutoModelForCausalLM
|
|
|
32 |
|
33 |
+
tokenizer = AutoTokenizer.from_pretrained("rinna/japanese-gpt-neox-small", use_fast=False)
|
34 |
model = GPTNeoXForCausalLM.from_pretrained("rinna/japanese-gpt-neox-small")
|
35 |
~~~~
|
36 |
|
config.json
CHANGED
@@ -1,42 +1,24 @@
|
|
1 |
{
|
2 |
-
"activation_function": "gelu",
|
3 |
"architectures": [
|
4 |
"GPTNeoXForCausalLM"
|
5 |
],
|
6 |
-
"attn_pdrop": 0.0,
|
7 |
"bos_token_id": 2,
|
8 |
-
"embd_pdrop": 0.0,
|
9 |
"eos_token_id": 3,
|
10 |
-
"
|
11 |
-
"
|
12 |
"initializer_range": 0.02,
|
13 |
-
"
|
14 |
-
"
|
15 |
-
"
|
16 |
-
"
|
17 |
-
"
|
18 |
-
"
|
19 |
-
"
|
20 |
-
"
|
21 |
-
"resid_pdrop": 0.0,
|
22 |
-
"rotary": true,
|
23 |
-
"rotary_dim": null,
|
24 |
-
"scale_attn_weights": true,
|
25 |
-
"summary_activation": null,
|
26 |
-
"summary_first_dropout": 0.1,
|
27 |
-
"summary_proj_to_labels": true,
|
28 |
-
"summary_type": "cls_index",
|
29 |
-
"summary_use_proj": true,
|
30 |
-
"task_specific_params": {
|
31 |
-
"text-generation": {
|
32 |
-
"do_sample": true,
|
33 |
-
"max_length": 50,
|
34 |
-
"temperature": 1.0
|
35 |
-
}
|
36 |
-
},
|
37 |
"tie_word_embeddings": false,
|
38 |
"tokenizer_class": "T5Tokenizer",
|
39 |
"torch_dtype": "float32",
|
40 |
"use_cache": true,
|
|
|
41 |
"vocab_size": 44416
|
42 |
}
|
|
|
1 |
{
|
|
|
2 |
"architectures": [
|
3 |
"GPTNeoXForCausalLM"
|
4 |
],
|
|
|
5 |
"bos_token_id": 2,
|
|
|
6 |
"eos_token_id": 3,
|
7 |
+
"hidden_act": "gelu",
|
8 |
+
"hidden_size": 768,
|
9 |
"initializer_range": 0.02,
|
10 |
+
"intermediate_size": 3072,
|
11 |
+
"layer_norm_eps": 1e-05,
|
12 |
+
"max_position_embeddings": 2048,
|
13 |
+
"model_type": "gpt_neox",
|
14 |
+
"num_attention_heads": 12,
|
15 |
+
"num_hidden_layers": 12,
|
16 |
+
"rotary_emb_base": 10000,
|
17 |
+
"rotary_pct": 1.0,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
18 |
"tie_word_embeddings": false,
|
19 |
"tokenizer_class": "T5Tokenizer",
|
20 |
"torch_dtype": "float32",
|
21 |
"use_cache": true,
|
22 |
+
"use_parallel_residual": false,
|
23 |
"vocab_size": 44416
|
24 |
}
|
pytorch_model.bin
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:58e3f25be62e0e5e860b36a4e9b1ef0bd9299378a488c1dafb48526222076d5b
|
3 |
+
size 663506641
|