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fix transformers 4.48.0

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This commit is contained in:
hypothesis-z 2025-01-20 15:06:12 +08:00
parent 3c406233cd
commit 99dfb3dfab
3 changed files with 6 additions and 9 deletions
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8
FlagEmbedding/inference/reranker/decoder_only/models/gemma_model.py
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@ -53,7 +53,7 @@ from transformers.utils import (
)
from .gemma_config import CostWiseGemmaConfig
from transformers.models.gemma2.modeling_gemma2 import Gemma2RMSNorm, Gemma2RotaryEmbedding, rotate_half, apply_rotary_pos_emb
from transformers.models.gemma2.modeling_gemma2 import Gemma2MLP, repeat_kv, Gemma2Attention, Gemma2FlashAttention2, Gemma2SdpaAttention, GEMMA2_ATTENTION_CLASSES, Gemma2DecoderLayer, GEMMA2_START_DOCSTRING
from transformers.models.gemma2.modeling_gemma2 import Gemma2MLP, repeat_kv, Gemma2Attention, Gemma2DecoderLayer, GEMMA2_START_DOCSTRING
from transformers.models.gemma2.modeling_gemma2 import GEMMA2_INPUTS_DOCSTRING
if is_flash_attn_2_available():
@ -105,12 +105,6 @@ class CostWiseGemma2PreTrainedModel(PreTrainedModel):
if module.padding_idx is not None:
module.weight.data[module.padding_idx].zero_()
GEMMA2_ATTENTION_CLASSES = {
"eager": Gemma2Attention,
"flash_attention_2": Gemma2FlashAttention2,
"sdpa": Gemma2SdpaAttention,
}
_CONFIG_FOR_DOC = "CostWiseGemmaConfig"

5
FlagEmbedding/inference/reranker/decoder_only/models/modeling_minicpm_reranker.py
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@ -41,7 +41,7 @@ from transformers.modeling_attn_mask_utils import (
from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, \
SequenceClassifierOutputWithPast
from transformers.modeling_utils import PreTrainedModel
from transformers.pytorch_utils import ALL_LAYERNORM_LAYERS, is_torch_greater_or_equal_than_1_13
from transformers.pytorch_utils import ALL_LAYERNORM_LAYERS
from transformers.utils import (
add_start_docstrings,
add_start_docstrings_to_model_forward,
@ -63,6 +63,9 @@ except:
# This makes `_prepare_4d_causal_attention_mask` a leaf function in the FX graph.
# It means that the function will not be traced through and simply appear as a node in the graph.
from packaging import version
parsed_torch_version_base = version.parse(version.parse(torch.__version__).base_version)
is_torch_greater_or_equal_than_1_13 = parsed_torch_version_base >= version.parse("1.13")
if is_torch_fx_available():
if not is_torch_greater_or_equal_than_1_13:
import torch.fx

2
setup.py
View File

@ -15,7 +15,7 @@ setup(
include_package_data=True,
install_requires=[
'torch>=1.6.0',
'transformers==4.44.2',
'transformers>=4.44.2',
'datasets==2.19.0',
'accelerate>=0.20.1',
'sentence_transformers',