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[Misc] Bump up transformers to v4.39.0 & Remove StarCoder2Config (#3551)

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Co-authored-by: Roy <jasonailu87@gmail.com>
Co-authored-by: Roger Meier <r.meier@siemens.com>
This commit is contained in:
Woosuk Kwon
2024-03-21 07:58:12 -07:00
committed by GitHub
parent 865732342b
commit c188ecb080
6 changed files with 3 additions and 76 deletions
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2
vllm/transformers_utils/configs/__init__.py
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@@ -4,13 +4,11 @@ from vllm.transformers_utils.configs.mpt import MPTConfig
# tiiuae/falcon-7b(-instruct) models. Newer Falcon models will use the
# `FalconConfig` class from the official HuggingFace transformers library.
from vllm.transformers_utils.configs.falcon import RWConfig
from vllm.transformers_utils.configs.starcoder2 import Starcoder2Config
from vllm.transformers_utils.configs.jais import JAISConfig
__all__ = [
"ChatGLMConfig",
"MPTConfig",
"RWConfig",
"Starcoder2Config",
"JAISConfig",
]

55
vllm/transformers_utils/configs/starcoder2.py
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@@ -1,55 +0,0 @@
from transformers import PretrainedConfig
class Starcoder2Config(PretrainedConfig):
model_type = "starcoder2"
keys_to_ignore_at_inference = ["past_key_values"]
def __init__(
self,
vocab_size=49152,
hidden_size=3072,
intermediate_size=12288,
num_hidden_layers=30,
num_attention_heads=24,
num_key_value_heads=2,
hidden_act="gelu_pytorch_tanh",
max_position_embeddings=4096,
initializer_range=0.018042,
norm_epsilon=1e-5,
use_cache=True,
bos_token_id=50256,
eos_token_id=50256,
rope_theta=10000.0,
sliding_window=None,
attention_dropout=0.0,
residual_dropout=0.0,
embedding_dropout=0.0,
use_bias=True,
**kwargs,
):
self.vocab_size = vocab_size
self.max_position_embeddings = max_position_embeddings
self.hidden_size = hidden_size
self.intermediate_size = intermediate_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.sliding_window = sliding_window
self.use_bias = use_bias
self.num_key_value_heads = num_key_value_heads
self.hidden_act = hidden_act
self.initializer_range = initializer_range
self.norm_epsilon = norm_epsilon
self.use_cache = use_cache
self.rope_theta = rope_theta
self.attention_dropout = attention_dropout
self.residual_dropout = residual_dropout
self.embedding_dropout = embedding_dropout
super().__init__(
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
**kwargs,
)
if self.architectures is None:
self.architectures = ['Starcoder2ForCausalLM']