diff --git a/server/poetry.lock b/server/poetry.lock index 89ad31e9..da8586ae 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -1,3 +1,5 @@ +# This file is automatically @generated by Poetry 1.4.0 and should not be changed by hand. + [[package]] name = "accelerate" version = "0.15.0" @@ -5,6 +7,10 @@ description = "Accelerate" category = "main" optional = false python-versions = ">=3.7.0" +files = [ + {file = "accelerate-0.15.0-py3-none-any.whl", hash = "sha256:014833307424cd0a22f89815802e00653756257c45dfdba2453e52d428931c65"}, + {file = "accelerate-0.15.0.tar.gz", hash = "sha256:438e25a01afa6e3ffbd25353e76a68be49677c3050f10bfac7beafaf53503efc"}, +] [package.dependencies] numpy = ">=1.17" @@ -18,9 +24,9 @@ dev = ["black (>=22.0,<23.0)", "datasets", "deepspeed (<0.7.0)", "evaluate", "fl quality = ["black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)"] rich = ["rich"] sagemaker = ["sagemaker"] -test_dev = ["datasets", "deepspeed (<0.7.0)", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"] -test_prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"] -test_trackers = ["comet-ml", "tensorboard", "wandb"] +test-dev = ["datasets", "deepspeed (<0.7.0)", "evaluate", "scikit-learn", "scipy", "tqdm", "transformers"] +test-prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"] +test-trackers = ["comet-ml", "tensorboard", "wandb"] testing = ["datasets", "deepspeed (<0.7.0)", "evaluate", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "tqdm", "transformers"] [[package]] @@ -30,14 +36,17 @@ description = "Classes Without Boilerplate" category = "dev" optional = false python-versions = ">=3.6" +files = [ + {file = "attrs-22.2.0-py3-none-any.whl", hash = "sha256:29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836"}, + {file = "attrs-22.2.0.tar.gz", hash = "sha256:c9227bfc2f01993c03f68db37d1d15c9690188323c067c641f1a35ca58185f99"}, +] [package.extras] cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"] dev = ["attrs[docs,tests]"] docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"] tests = ["attrs[tests-no-zope]", "zope.interface"] -tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=0.971,<0.990)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -tests_no_zope = ["cloudpickle", "hypothesis", "mypy (>=0.971,<0.990)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +tests-no-zope = ["cloudpickle", "cloudpickle", "hypothesis", "hypothesis", "mypy (>=0.971,<0.990)", "mypy (>=0.971,<0.990)", "pympler", "pympler", "pytest (>=4.3.0)", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-mypy-plugins", "pytest-xdist[psutil]", "pytest-xdist[psutil]"] [[package]] name = "backoff" @@ -46,6 +55,10 @@ description = "Function decoration for backoff and retry" category = "main" optional = false python-versions = ">=3.7,<4.0" +files = [ + {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"}, + {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"}, +] [[package]] name = "bitsandbytes" @@ -54,6 +67,10 @@ description = "8-bit optimizers and matrix multiplication routines." category = "main" optional = false python-versions = "*" +files = [ + {file = "bitsandbytes-0.35.4-py3-none-any.whl", hash = "sha256:201f168538ccfbd7594568a2f86c149cec8352782301076a15a783695ecec7fb"}, + {file = "bitsandbytes-0.35.4.tar.gz", hash = "sha256:b23db6b91cd73cb14faf9841a66bffa5c1722f9b8b57039ef2fb461ac22dd2a6"}, +] [[package]] name = "certifi" @@ -62,6 +79,10 @@ description = "Python package for providing Mozilla's CA Bundle." category = "main" optional = false python-versions = ">=3.6" +files = [ + {file = "certifi-2022.12.7-py3-none-any.whl", hash = "sha256:4ad3232f5e926d6718ec31cfc1fcadfde020920e278684144551c91769c7bc18"}, + {file = "certifi-2022.12.7.tar.gz", hash = "sha256:35824b4c3a97115964b408844d64aa14db1cc518f6562e8d7261699d1350a9e3"}, +] [[package]] name = "charset-normalizer" @@ -70,590 +91,7 @@ description = "The Real First Universal Charset Detector. 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b/server/text_generation_server/models/__init__.py index 3e2f5c66..23f7af9d 100644 --- a/server/text_generation_server/models/__init__.py +++ b/server/text_generation_server/models/__init__.py @@ -9,6 +9,7 @@ from text_generation_server.models.bloom import BLOOM, BLOOMSharded from text_generation_server.models.seq2seq_lm import Seq2SeqLM from text_generation_server.models.galactica import Galactica, GalacticaSharded from text_generation_server.models.santacoder import SantaCoder +from text_generation_server.models.llama import Llama from text_generation_server.models.gpt_neox import GPTNeoxSharded from text_generation_server.models.t5 import T5Sharded @@ -22,6 +23,7 @@ __all__ = [ "GPTNeoxSharded", "Seq2SeqLM", "SantaCoder", + "Llama", "T5Sharded", "get_model", ] @@ -69,6 +71,12 @@ def get_model( else: return Seq2SeqLM(model_id, revision, quantize=quantize) + if config.model_type == "llama": + if sharded: + raise ValueError("sharded is not supported for Llama") + else: + return Llama(model_id, revision, quantize) + if sharded: raise ValueError("sharded is not supported for AutoModel") try: diff --git a/server/text_generation_server/models/llama.py b/server/text_generation_server/models/llama.py new file mode 100644 index 00000000..7147211c --- /dev/null +++ b/server/text_generation_server/models/llama.py @@ -0,0 +1,41 @@ +import torch + +from transformers import LlamaTokenizer, LlamaForCausalLM +from typing import Optional +from text_generation_server.models import CausalLM + + +class Llama(CausalLM): + def __init__( + self, model_id: str, revision: Optional[str] = None, quantize: bool = False + ): + if torch.cuda.is_available(): + device = torch.device("cuda") + dtype = torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float32 + else: + if quantize: + raise ValueError("quantization is not available on CPU") + + device = torch.device("cpu") + dtype = torch.float32 + + tokenizer = LlamaTokenizer.from_pretrained( + model_id, revision=revision, padding_side="left" + ) + self.model = LlamaForCausalLM.from_pretrained( + model_id, + revision=revision, + torch_dtype=dtype, + device_map="auto" if torch.cuda.is_available() else None, + load_in_8bit=quantize, + ).eval() + tokenizer.pad_token_id = ( + self.model.config.pad_token_id + if self.model.config.pad_token_id is not None + else self.model.config.eos_token_id + ) + + super(CausalLM, self).__init__( + tokenizer=tokenizer, + device=device, + ) \ No newline at end of file