text-generation-inference/server/text_generation_server/models/bloom.py
Karol Damaszke 7342baa2eb
Add support for rope_scaling and remove is_optimized_for_gaudi (#112)
Co-authored-by: Karol Damaszke <kdamaszke@habana.ai>
2024-03-29 15:07:32 +01:00

47 lines
1.1 KiB
Python

import torch
from typing import Optional, Type
from transformers import PreTrainedTokenizerBase
from text_generation_server.models import CausalLM
from text_generation_server.models.causal_lm import CausalLMBatch
from text_generation_server.pb import generate_pb2
class BloomCausalLMBatch(CausalLMBatch):
@classmethod
def from_pb(
cls,
pb: generate_pb2.Batch,
tokenizer: PreTrainedTokenizerBase,
dtype: torch.dtype,
device: torch.device,
) -> "CausalLMBatch":
batch = super().from_pb(
pb=pb,
tokenizer=tokenizer,
dtype=dtype,
device=device,
)
batch.keys_head_dim_last = False
return batch
class BLOOM(CausalLM):
def __init__(
self,
model_id: str,
revision: Optional[str] = None,
dtype: Optional[torch.dtype] = None,
):
super(BLOOM, self).__init__(
model_id=model_id,
revision=revision,
dtype=dtype,
)
@property
def batch_type(self) -> Type[CausalLMBatch]:
return BloomCausalLMBatch