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Deprecate unused OpenLlama architecture (#24922)
* Resolve typo in check_repo.py * Specify encoding when opening modeling files * Deprecate the OpenLlama architecture * Add disclaimer pointing to Llama I'm open to different wordings here * Match the capitalisation of LLaMA
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‎docs/source/en/model_doc/open-llama.md‎

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# Open-Llama
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<Tip warning={true}>
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This model is in maintenance mode only, so we won't accept any new PRs changing its code.
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If you run into any issues running this model, please reinstall the last version that supported this model: v4.31.0.
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You can do so by running the following command: `pip install -U transformers==4.31.0`.
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</Tip>
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<Tip warning={true}>
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This model differs from the [OpenLLaMA models](https://huggingface.co/models?search=openllama) on the Hugging Face Hub, which primarily use the [LLaMA](llama) architecture.
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</Tip>
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## Overview
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The Open-Llama model was proposed in [Open-Llama project](https://github.com/s-JoL/Open-Llama) by community developer s-JoL.

‎src/transformers/__init__.py‎

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"MCTCTProcessor",
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],
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"models.deprecated.mmbt": ["MMBTConfig"],
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"models.deprecated.open_llama": ["OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenLlamaConfig"],
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"models.deprecated.retribert": [
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"RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
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"RetriBertConfig",
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"NystromformerConfig",
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],
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"models.oneformer": ["ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "OneFormerConfig", "OneFormerProcessor"],
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"models.open_llama": ["OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenLlamaConfig"],
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"models.openai": ["OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OpenAIGPTConfig", "OpenAIGPTTokenizer"],
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"models.opt": ["OPTConfig"],
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"models.owlvit": [
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]
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)
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_import_structure["models.deprecated.mmbt"].extend(["MMBTForClassification", "MMBTModel", "ModalEmbeddings"])
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_import_structure["models.deprecated.open_llama"].extend(
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["OpenLlamaForCausalLM", "OpenLlamaForSequenceClassification", "OpenLlamaModel", "OpenLlamaPreTrainedModel"]
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)
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_import_structure["models.deprecated.retribert"].extend(
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["RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST", "RetriBertModel", "RetriBertPreTrainedModel"]
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)
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"OneFormerPreTrainedModel",
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]
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)
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_import_structure["models.open_llama"].extend(
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["OpenLlamaForCausalLM", "OpenLlamaForSequenceClassification", "OpenLlamaModel", "OpenLlamaPreTrainedModel"]
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)
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_import_structure["models.openai"].extend(
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[
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"OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST",
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MCTCTProcessor,
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)
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from .models.deprecated.mmbt import MMBTConfig
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from .models.deprecated.open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig
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from .models.deprecated.retribert import (
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RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
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RetriBertConfig,
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from .models.nllb_moe import NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP, NllbMoeConfig
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from .models.nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig
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from .models.oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig, OneFormerProcessor
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from .models.open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig
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from .models.openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig, OpenAIGPTTokenizer
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from .models.opt import OPTConfig
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from .models.owlvit import (
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MCTCTPreTrainedModel,
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)
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from .models.deprecated.mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings
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from .models.deprecated.open_llama import (
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OpenLlamaForCausalLM,
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OpenLlamaForSequenceClassification,
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OpenLlamaModel,
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OpenLlamaPreTrainedModel,
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)
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from .models.deprecated.retribert import (
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RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
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RetriBertModel,
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OneFormerModel,
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OneFormerPreTrainedModel,
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)
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from .models.open_llama import (
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OpenLlamaForCausalLM,
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OpenLlamaForSequenceClassification,
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OpenLlamaModel,
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OpenLlamaPreTrainedModel,
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)
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from .models.openai import (
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OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
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OpenAIGPTDoubleHeadsModel,

‎src/transformers/models/__init__.py‎

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nllb_moe,
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nystromformer,
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oneformer,
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open_llama,
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openai,
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opt,
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owlvit,

‎src/transformers/models/auto/configuration_auto.py‎

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"bort",
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"mctct",
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"mmbt",
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"open_llama",
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"retribert",
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"tapex",
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"trajectory_transformer",

‎src/transformers/models/open_llama/__init__.py‎ renamed to ‎src/transformers/models/deprecated/open_llama/__init__.py‎

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# limitations under the License.
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from typing import TYPE_CHECKING
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from ...utils import (
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from ....utils import (
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OptionalDependencyNotAvailable,
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_LazyModule,
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is_sentencepiece_available,

‎src/transformers/models/open_llama/configuration_open_llama.py‎ renamed to ‎src/transformers/models/deprecated/open_llama/configuration_open_llama.py‎

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# limitations under the License.
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""" Open-Llama model configuration"""
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from ...configuration_utils import PretrainedConfig
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from ...utils import logging
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from ....configuration_utils import PretrainedConfig
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from ....utils import logging
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logger = logging.get_logger(__name__)

‎src/transformers/models/open_llama/modeling_open_llama.py‎ renamed to ‎src/transformers/models/deprecated/open_llama/modeling_open_llama.py‎

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from torch import nn
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from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
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from ...activations import ACT2FN
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from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, SequenceClassifierOutputWithPast
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from ...modeling_utils import PreTrainedModel
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from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
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from ....activations import ACT2FN
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from ....modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, SequenceClassifierOutputWithPast
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from ....modeling_utils import PreTrainedModel
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from ....utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
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from .configuration_open_llama import OpenLlamaConfig
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‎src/transformers/utils/dummy_pt_objects.py‎

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requires_backends(self, ["torch"])
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class OpenLlamaForCausalLM(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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class OpenLlamaForSequenceClassification(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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class OpenLlamaModel(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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class OpenLlamaPreTrainedModel(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
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requires_backends(self, ["torch"])
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class OpenLlamaForCausalLM(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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class OpenLlamaForSequenceClassification(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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class OpenLlamaModel(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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class OpenLlamaPreTrainedModel(metaclass=DummyObject):
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_backends = ["torch"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["torch"])
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OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST = None
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‎tests/models/open_llama/__init__.py‎

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