first commit
Browse files- config.json +71 -0
- configuration_olmo.py +65 -0
- generation_config.json +6 -0
- model.safetensors +3 -0
config.json
ADDED
@@ -0,0 +1,71 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "/nfs100/dongyh/FANformer-1B",
|
3 |
+
"activation_type": "swiglu",
|
4 |
+
"alibi": false,
|
5 |
+
"alibi_bias_max": 8.0,
|
6 |
+
"architectures": [
|
7 |
+
"OLMoForCausalLM"
|
8 |
+
],
|
9 |
+
"att_nolinear": false,
|
10 |
+
"attention_activation": null,
|
11 |
+
"attention_dropout": 0.0,
|
12 |
+
"attention_layer_norm": false,
|
13 |
+
"attention_layer_norm_with_affine": false,
|
14 |
+
"auto_map": {
|
15 |
+
"AutoConfig": "configuration_olmo.OLMoConfig",
|
16 |
+
"AutoModelForCausalLM": "modeling_fan.OLMoForCausalLM"
|
17 |
+
},
|
18 |
+
"bias_for_layer_norm": false,
|
19 |
+
"block_group_size": 1,
|
20 |
+
"block_type": "sequential",
|
21 |
+
"clip_qkv": null,
|
22 |
+
"d_model": 2048,
|
23 |
+
"emb_init_std": null,
|
24 |
+
"embedding_dropout": 0.0,
|
25 |
+
"embedding_layer_norm": false,
|
26 |
+
"embedding_size": 50304,
|
27 |
+
"eos_token_id": 50279,
|
28 |
+
"ffn_activation": null,
|
29 |
+
"flash_attention": true,
|
30 |
+
"include_bias": false,
|
31 |
+
"init_cutoff_factor": null,
|
32 |
+
"init_device": "cuda",
|
33 |
+
"init_fn": "mitchell",
|
34 |
+
"init_std": 0.02,
|
35 |
+
"layer_norm_eps": 1e-06,
|
36 |
+
"layer_norm_type": "rms",
|
37 |
+
"layer_norm_with_affine": true,
|
38 |
+
"max_sequence_length": 2048,
|
39 |
+
"mlp_hidden_size": null,
|
40 |
+
"mlp_ratio": 8,
|
41 |
+
"model_type": "hf_olmo",
|
42 |
+
"multi_query_attention": false,
|
43 |
+
"n_heads": 16,
|
44 |
+
"n_kv_heads": null,
|
45 |
+
"n_layers": 16,
|
46 |
+
"nofanbias": false,
|
47 |
+
"nonorm1": false,
|
48 |
+
"norm_after": false,
|
49 |
+
"p_ratio": 0.25,
|
50 |
+
"pad_token_id": 1,
|
51 |
+
"precision": "amp_bf16",
|
52 |
+
"residual_dropout": 0.0,
|
53 |
+
"rope": true,
|
54 |
+
"rope_full_precision": true,
|
55 |
+
"rope_theta": 10000,
|
56 |
+
"scale_emb_init": false,
|
57 |
+
"scale_logits": false,
|
58 |
+
"torch_dtype": "float32",
|
59 |
+
"transformers_version": "4.49.0",
|
60 |
+
"use_A": false,
|
61 |
+
"use_ATF": true,
|
62 |
+
"use_cache": true,
|
63 |
+
"use_fpn": false,
|
64 |
+
"use_fpneq": false,
|
65 |
+
"use_fpnnow": false,
|
66 |
+
"use_fpnpn": false,
|
67 |
+
"use_mod": false,
|
68 |
+
"use_mod_ffn": 0,
|
69 |
+
"vocab_size": 50280,
|
70 |
+
"weight_tying": true
|
71 |
+
}
|
configuration_olmo.py
ADDED
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""
|
2 |
+
OLMo configuration
|
3 |
+
"""
|
4 |
+
|
5 |
+
from transformers import AutoConfig, PretrainedConfig
|
6 |
+
from transformers.utils import logging
|
7 |
+
|
8 |
+
from olmo.config import ModelConfig
|
9 |
+
from olmo.exceptions import OLMoConfigurationError
|
10 |
+
|
11 |
+
logger = logging.get_logger(__name__)
|
12 |
+
|
13 |
+
|
14 |
+
class OLMoConfig(PretrainedConfig):
|
15 |
+
model_type = "hf_olmo"
|
16 |
+
keys_to_ignore_at_inference = ["past_key_values"] # TODO: confirm
|
17 |
+
|
18 |
+
def __init__(self, use_cache: bool = False, **kwargs):
|
19 |
+
model_config = ModelConfig()
|
20 |
+
all_kwargs = model_config.asdict()
|
21 |
+
all_kwargs.update(kwargs)
|
22 |
+
all_kwargs.update({"use_cache": use_cache})
|
23 |
+
all_kwargs.update(
|
24 |
+
{"architectures": all_kwargs.get("architectures", ["OLMoForCausalLM"]) or ["OLMoForCausalLM"]}
|
25 |
+
)
|
26 |
+
super().__init__(**all_kwargs)
|
27 |
+
|
28 |
+
@property
|
29 |
+
def num_attention_heads(self):
|
30 |
+
return self.n_heads
|
31 |
+
|
32 |
+
@property
|
33 |
+
def num_hidden_layers(self):
|
34 |
+
return self.n_layers
|
35 |
+
|
36 |
+
@property
|
37 |
+
def hidden_size(self):
|
38 |
+
return self.d_model
|
39 |
+
|
40 |
+
@property
|
41 |
+
def effective_n_kv_heads(self) -> int:
|
42 |
+
if self.n_kv_heads is None:
|
43 |
+
if self.multi_query_attention is True:
|
44 |
+
return 1
|
45 |
+
else:
|
46 |
+
return self.n_heads
|
47 |
+
else:
|
48 |
+
if self.multi_query_attention is None:
|
49 |
+
return self.n_kv_heads
|
50 |
+
if self.multi_query_attention:
|
51 |
+
n_kv_heads_should_be = 1
|
52 |
+
else:
|
53 |
+
n_kv_heads_should_be = self.n_heads
|
54 |
+
if self.n_kv_heads == n_kv_heads_should_be:
|
55 |
+
return n_kv_heads_should_be
|
56 |
+
else:
|
57 |
+
raise OLMoConfigurationError(
|
58 |
+
"You can't set `multi_query_attention` and `n_kv_heads` at the same time."
|
59 |
+
)
|
60 |
+
|
61 |
+
|
62 |
+
# Register the config class so that it is available for transformer pipelines, auto-loading etc.
|
63 |
+
# OLMo is integrated directly in transformers from v4.40.0 onwards, but the version in transformers
|
64 |
+
# may not support the newest architectures we create.
|
65 |
+
AutoConfig.register("hf_olmo", OLMoConfig)
|
generation_config.json
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_from_model_config": true,
|
3 |
+
"eos_token_id": 50279,
|
4 |
+
"pad_token_id": 1,
|
5 |
+
"transformers_version": "4.49.0"
|
6 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:abfcfa6274cec50b52ef98b4c541d8c7738c2d19bc146526114d71e55316312b
|
3 |
+
size 4908768976
|