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from llama_index.core.readers.base import BaseReader from llama_index.readers.kaltura_esearch import KalturaESearchReader def test_class(): names_of_base_classes = [b.__name__ for b in KalturaESearchReader.__mro__] assert BaseReader.__name__ in names_of_base_classes
llama_index/llama-index-integrations/readers/llama-index-readers-kaltura/tests/test_readers_kaltura.py/0
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import "@/styles/globals.css"; import { useState } from "react"; import type { AppProps } from "next/app"; import { createBrowserSupabaseClient } from "@supabase/auth-helpers-nextjs"; import { SessionContextProvider } from "@supabase/auth-helpers-react"; function App({ Component, pageProps }: AppProps) { return <Com...
langchain-template-supabase/src/pages/_app.tsx/0
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- sections: - local: index title: Home - local: quickstart title: Quickstart - local: installation title: Installation title: Get started - sections: - local: feature_extraction title: Using Pretrained Models as Feature Extractors - local: training_script title: Training With The Offici...
pytorch-image-models/hfdocs/source/_toctree.yml/0
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# Atlas >[Nomic Atlas](https://docs.nomic.ai/index.html) is a platform for interacting with both > small and internet scale unstructured datasets. ## Installation and Setup - Install the Python package with `pip install nomic` - `Nomic` is also included in langchains poetry extras `poetry install -E all` ## Vect...
langchain/docs/docs/integrations/providers/atlas.mdx/0
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from llama_index.embeddings.bedrock.base import BedrockEmbedding, Models __all__ = ["BedrockEmbedding", "Models"]
llama_index/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/llama_index/embeddings/bedrock/__init__.py/0
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 1, "logprob": null, "text": "<s>" }, { "id": 3735, "logprob": -12.9140625, "text": "Test" }, { "id": 2...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral.json/0
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from langchain_community.document_loaders.modern_treasury import ( ModernTreasuryLoader, ) __all__ = ["ModernTreasuryLoader"]
langchain/libs/langchain/langchain/document_loaders/modern_treasury.py/0
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from langchain_community.utilities.scenexplain import SceneXplainAPIWrapper __all__ = ["SceneXplainAPIWrapper"]
langchain/libs/langchain/langchain/utilities/scenexplain.py/0
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// Code generated by mockery v2.32.4. DO NOT EDIT. package datacoord import ( datapb "github.com/milvus-io/milvus/internal/proto/datapb" mock "github.com/stretchr/testify/mock" ) // MockScheduler is an autogenerated mock type for the Scheduler type type MockScheduler struct { mock.Mock } type MockScheduler_Expec...
milvus/internal/datacoord/mock_scheduler.go/0
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from typing import Any, Dict, List, Sequence, Set from uuid import UUID from chromadb.config import Settings, System from chromadb.ingest import CollectionAssignmentPolicy, Consumer from chromadb.proto.chroma_pb2_grpc import ( # SegmentServerServicer, # add_SegmentServerServicer_to_server, VectorReaderServi...
chroma/chromadb/segment/impl/distributed/server.py/0
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from langchain_community.embeddings.jina import JinaEmbeddings __all__ = ["JinaEmbeddings"]
langchain/libs/langchain/langchain/embeddings/jina.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/pipelines/controlnet/test_controlnet_sdxl_img2img.py/0
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import type { OpenAIClient } from "@langchain/openai"; import { BaseChatModel, type BaseChatModelParams, } from "@langchain/core/language_models/chat_models"; import { AIMessage, BaseMessage, ChatMessage, HumanMessage, } from "@langchain/core/messages"; import { ChatResult, ChatGeneration } from "@langchai...
langchainjs/libs/langchain-community/src/chat_models/minimax.ts/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/transformers_agents.md/0
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"""Module for defining/enumerating the common sections from SEC forms.""" import re from enum import Enum from typing import List class SECSection(Enum): PROSPECTUS_SUMMARY = re.compile(r"^(?:prospectus )?summary$") ABOUT_PROSPECTUS = re.compile(r"about this prospectus") FORWARD_LOOKING_STATEMENTS = re.co...
llama_index/llama-index-integrations/readers/llama-index-readers-sec-filings/llama_index/readers/sec_filings/prepline_sec_filings/sections.py/0
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package proxy import ( "context" "github.com/cockroachdb/errors" "go.uber.org/zap" "golang.org/x/sync/errgroup" "github.com/milvus-io/milvus/internal/types" "github.com/milvus-io/milvus/pkg/log" "github.com/milvus-io/milvus/pkg/util/merr" ) // type pickShardPolicy func(ctx context.Context, mgr shardClientMgr...
milvus/internal/proxy/task_policies.go/0
{ "file_path": "milvus/internal/proxy/task_policies.go", "repo_id": "milvus", "token_count": 736 }
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from langchain_community.utilities.pubmed import PubMedAPIWrapper __all__ = ["PubMedAPIWrapper"]
langchain/libs/langchain/langchain/utilities/pubmed.py/0
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<jupyter_start><jupyter_text>Managed Index with Zilliz Cloud Pipelines[Zilliz Cloud Pipelines](https://docs.zilliz.com/docs/pipelines) is a scalable API service for retrieval. You can use Zilliz Cloud Pipelines as managed index in `llama-index`. This service can transform documents into vector embeddings and store them...
llama_index/docs/examples/managed/zcpDemo.ipynb/0
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"""Test Neo4jVector functionality.""" import os from typing import List from langchain_core.documents import Document from langchain_community.vectorstores.neo4j_vector import ( Neo4jVector, SearchType, _get_search_index_query, ) from langchain_community.vectorstores.utils import DistanceStrategy from tes...
langchain/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py/0
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<jupyter_start><jupyter_text>Evaluation using [Prometheus](https://huggingface.co/TheBloke/prometheus-13B-v1.0-GPTQ) model Evaluation is a crucial aspect of iterating over your RAG (Retrieval-Augmented Generation) pipeline. This process has relied heavily on GPT-4. However, a new open-source model named [Prometheus](ht...
llama_index/docs/examples/evaluation/prometheus_evaluation.ipynb/0
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# Process audio data This guide shows specific methods for processing audio datasets. Learn how to: - Resample the sampling rate. - Use [`~Dataset.map`] with audio datasets. For a guide on how to process any type of dataset, take a look at the <a class="underline decoration-sky-400 decoration-2 font-semibold" href="...
datasets/docs/source/audio_process.mdx/0
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from langchain_community.tools.azure_cognitive_services.image_analysis import ( AzureCogsImageAnalysisTool, ) __all__ = ["AzureCogsImageAnalysisTool"]
langchain/libs/langchain/langchain/tools/azure_cognitive_services/image_analysis.py/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ja/custom_models.md/0
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"""DuckDuckGo Search API toolkit.""" from langchain_community.tools.ddg_search.tool import DuckDuckGoSearchRun __all__ = ["DuckDuckGoSearchRun"]
langchain/libs/langchain/langchain/tools/ddg_search/__init__.py/0
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import contextlib import os import sqlite3 import pytest from datasets import Dataset, Features, Value from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy def _check_sql_dataset(dataset, expected_f...
datasets/tests/io/test_sql.py/0
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<jupyter_start><jupyter_text>SQLite-VSS>[SQLite-VSS](https://alexgarcia.xyz/sqlite-vss/) is an `SQLite` extension designed for vector search, emphasizing local-first operations and easy integration into applications without external servers. Leveraging the `Faiss` library, it offers efficient similarity search and clus...
langchain/docs/docs/integrations/vectorstores/sqlitevss.ipynb/0
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import { Document } from "@langchain/core/documents"; import { getEnvironmentVariable } from "@langchain/core/utils/env"; import { BaseDocumentLoader } from "../base.js"; /** * Interface representing the parameters for the SerpAPI loader. It * includes properties such as the search query and the API key. */ interfa...
langchainjs/langchain/src/document_loaders/web/serpapi.ts/0
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# LlamaIndex Embeddings Integration: Adapter
llama_index/llama-index-integrations/embeddings/llama-index-embeddings-adapter/README.md/0
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python_sources()
llama_index/llama-index-core/llama_index/core/langchain_helpers/BUILD/0
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"""Test Aleph Alpha specific stuff.""" import pytest from langchain_core.pydantic_v1 import SecretStr from pytest import CaptureFixture, MonkeyPatch from langchain_community.llms.aleph_alpha import AlephAlpha @pytest.mark.requires("aleph_alpha_client") def test_api_key_is_secret_string() -> None: llm = AlephAlp...
langchain/libs/community/tests/unit_tests/llms/test_aleph_alpha.py/0
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from typing import Any, Dict, Optional from llama_index.core.base.llms.types import LLMMetadata from llama_index.core.bridge.pydantic import Field from llama_index.core.constants import ( DEFAULT_CONTEXT_WINDOW, DEFAULT_NUM_OUTPUTS, DEFAULT_TEMPERATURE, ) from llama_index.core.llms.generic_utils import get...
llama_index/llama-index-integrations/llms/llama-index-llms-openrouter/llama_index/llms/openrouter/base.py/0
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[tool.poetry] name = "rag-gpt-crawler" version = "0.1.0" description = "Use gpt-crawler to build a chat app for any website" authors = [ "Lance Martin <lance@langchain.dev>", ] readme = "README.md" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" langchain = "^0.1" openai = "<2" tiktoken = ">=0.5.1" chromadb = "...
langchain/templates/rag-gpt-crawler/pyproject.toml/0
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// Copyright (C) 2019-2020 Zilliz. All rights reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance // with the License. You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable l...
milvus/internal/mq/mqimpl/rocksmq/client/error.go/0
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from .cosine_lr import CosineLRScheduler from .multistep_lr import MultiStepLRScheduler from .plateau_lr import PlateauLRScheduler from .poly_lr import PolyLRScheduler from .step_lr import StepLRScheduler from .tanh_lr import TanhLRScheduler from .scheduler_factory import create_scheduler, create_scheduler_v2, schedul...
pytorch-image-models/timm/scheduler/__init__.py/0
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"""Tool for Steam Web API""" from typing import Optional from langchain_core.callbacks import CallbackManagerForToolRun from langchain_core.tools import BaseTool from langchain_community.utilities.steam import SteamWebAPIWrapper class SteamWebAPIQueryRun(BaseTool): """Tool that searches the Steam Web API.""" ...
langchain/libs/community/langchain_community/tools/steam/tool.py/0
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from importlib import metadata from langchain_core._api import ( surface_langchain_beta_warnings, surface_langchain_deprecation_warnings, ) try: __version__ = metadata.version(__package__) except metadata.PackageNotFoundError: # Case where package metadata is not available. __version__ = "" surfa...
langchain/libs/core/langchain_core/__init__.py/0
{ "file_path": "langchain/libs/core/langchain_core/__init__.py", "repo_id": "langchain", "token_count": 125 }
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[tool.poetry] name = "langchain-community" version = "0.0.20" description = "Community contributed LangChain integrations." authors = [] license = "MIT" readme = "README.md" repository = "https://github.com/langchain-ai/langchain" [tool.poetry.dependencies] python = ">=3.8.1,<4.0" langchain-core = ">=0.1.21,<0.2" SQLA...
langchain/libs/community/pyproject.toml/0
{ "file_path": "langchain/libs/community/pyproject.toml", "repo_id": "langchain", "token_count": 4129 }
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import builtins import json from typing import Optional, Type from langchain_core.callbacks import AsyncCallbackManagerForToolRun from langchain_core.pydantic_v1 import BaseModel, Field from langchain_community.tools.ainetwork.base import AINBaseTool, OperationType class RuleSchema(BaseModel): """Schema for own...
langchain/libs/community/langchain_community/tools/ainetwork/rule.py/0
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# LlamaIndex Embeddings Integration: Llm Rails
llama_index/llama-index-integrations/embeddings/llama-index-embeddings-llm-rails/README.md/0
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# Multi Subject Dreambooth for Inpainting Models Please note that this project is not actively maintained. However, you can open an issue and tag @gzguevara. [DreamBooth](https://arxiv.org/abs/2208.12242) is a method to personalize text2image models like stable diffusion given just a few(3~5) images of a subject. Thi...
diffusers/examples/research_projects/multi_subject_dreambooth_inpainting/README.md/0
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from langchain_community.llms.forefrontai import ForefrontAI __all__ = ["ForefrontAI"]
langchain/libs/langchain/langchain/llms/forefrontai.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/examples/consistency_distillation/test_lcm_lora.py/0
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poetry_requirements( name="poetry", )
llama_index/llama-index-integrations/llms/llama-index-llms-replicate/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-replicate/BUILD", "repo_id": "llama_index", "token_count": 18 }
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{ "dataPrompt": { "preamble": "Given a product description, you should return a name for that product that includes something about rainbows.", "columns": [ { "columnId": "CFA438B7-313B-4A50-AF74-3ACBC9216A4B", "displayName": "description:", "isInput": true }, { ...
langchainjs/langchain/src/experimental/hubs/makersuite/tests/googlemakersuite-files/dataPrompt.json/0
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poetry_requirements( name="poetry", )
llama_index/llama-index-integrations/readers/llama-index-readers-dad-jokes/BUILD/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-dad-jokes/BUILD", "repo_id": "llama_index", "token_count": 18 }
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package msgstream import ( "context" "fmt" "math/rand" "os" "sync" "testing" "github.com/stretchr/testify/assert" "github.com/milvus-io/milvus/pkg/mq/msgstream/mqwrapper" "github.com/milvus-io/milvus/pkg/mq/msgstream/mqwrapper/nmq" "github.com/milvus-io/milvus/pkg/util/funcutil" "github.com/milvus-io/milv...
milvus/pkg/mq/msgstream/stream_bench_test.go/0
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<jupyter_start><jupyter_text>Slack>[Slack](https://slack.com/) is an instant messaging program.This notebook covers how to load documents from a Zipfile generated from a `Slack` export.In order to get this `Slack` export, follow these instructions: 🧑 Instructions for ingesting your own datasetExport your Slack data. Y...
langchain/docs/docs/integrations/document_loaders/slack.ipynb/0
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<jupyter_start><jupyter_text>Azure OpenAI If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-llms-azure-openai !pip install llama-index<jupyter_output><empty_output><jupyter_text>Prerequisites 1. Setup an Azure subscription - you can create o...
llama_index/docs/examples/llm/azure_openai.ipynb/0
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import type { CloseVectorSaveableVectorStore } from "closevector-common"; import type { EmbeddingsInterface } from "@langchain/core/embeddings"; import { Document } from "@langchain/core/documents"; import { SaveableVectorStore } from "@langchain/core/vectorstores"; type CloseVectorCredentials = { key?: string; s...
langchainjs/libs/langchain-community/src/vectorstores/closevector/common.ts/0
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<jupyter_start><jupyter_text>Azure CosmosDB MongoDB Vector StoreIn this notebook we are going to show how to use Azure Cosmosdb Mongodb vCore to perform vector searches in LlamaIndex. We will create the embedding using Azure Open AI. If you're opening this Notebook on colab, you will probably need to install LlamaInde...
llama_index/docs/examples/vector_stores/AzureCosmosDBMongoDBvCoreDemo.ipynb/0
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--- sidebar_label: Fireworks --- import CodeBlock from "@theme/CodeBlock"; # Fireworks import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx"; <IntegrationInstallTooltip></IntegrationInstallTooltip> ```bash npm2yarn npm install @langchain/community ``` You can use models provided ...
langchainjs/docs/core_docs/docs/integrations/llms/fireworks.mdx/0
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from __future__ import annotations import time from itertools import repeat from typing import Any, Dict, Iterable, List, Optional, Tuple, Type from langchain_core.documents import Document from langchain_core.embeddings import Embeddings from langchain_core.vectorstores import VectorStore class XataVectorStore(Vec...
langchain/libs/community/langchain_community/vectorstores/xata.py/0
{ "file_path": "langchain/libs/community/langchain_community/vectorstores/xata.py", "repo_id": "langchain", "token_count": 4243 }
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<jupyter_start><jupyter_text>TF-IDF>[TF-IDF](https://scikit-learn.org/stable/modules/feature_extraction.htmltfidf-term-weighting) means term-frequency times inverse document-frequency.This notebook goes over how to use a retriever that under the hood uses [TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf) using `sc...
langchain/docs/docs/integrations/retrievers/tf_idf.ipynb/0
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from typing import Any, Callable, Dict, Optional, Sequence from llama_index.core.base.llms.types import ( ChatMessage, ChatResponse, ChatResponseAsyncGen, ChatResponseGen, CompletionResponse, CompletionResponseAsyncGen, CompletionResponseGen, LLMMetadata, MessageRole, ) from llama_i...
llama_index/llama-index-integrations/llms/llama-index-llms-vertex/llama_index/llms/vertex/base.py/0
{ "file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-vertex/llama_index/llms/vertex/base.py", "repo_id": "llama_index", "token_count": 5655 }
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#!/usr/bin/env python # coding=utf-8 # Copyright 2022 {{cookiecutter.authors}} and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http...
transformers/templates/adding_a_new_example_script/{{cookiecutter.directory_name}}/run_{{cookiecutter.example_shortcut}}.py/0
{ "file_path": "transformers/templates/adding_a_new_example_script/{{cookiecutter.directory_name}}/run_{{cookiecutter.example_shortcut}}.py", "repo_id": "transformers", "token_count": 15166 }
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"""Test CerebriumAI API wrapper.""" from langchain_community.llms.cerebriumai import CerebriumAI def test_cerebriumai_call() -> None: """Test valid call to cerebriumai.""" llm = CerebriumAI(max_length=10) output = llm("Say foo:") assert isinstance(output, str)
langchain/libs/community/tests/integration_tests/llms/test_cerebriumai.py/0
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from llama_index.legacy.extractors.interface import BaseExtractor from llama_index.legacy.extractors.marvin_metadata_extractor import ( MarvinMetadataExtractor, ) from llama_index.legacy.extractors.metadata_extractors import ( EntityExtractor, KeywordExtractor, PydanticProgramExtractor, QuestionsAns...
llama_index/llama-index-legacy/llama_index/legacy/extractors/__init__.py/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/extractors/__init__.py", "repo_id": "llama_index", "token_count": 223 }
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"""Wrapper around EdenAI's Generation API.""" import logging from typing import Any, Dict, List, Literal, Optional from aiohttp import ClientSession from langchain_core.callbacks import ( AsyncCallbackManagerForLLMRun, CallbackManagerForLLMRun, ) from langchain_core.language_models.llms import LLM from langcha...
langchain/libs/community/langchain_community/llms/edenai.py/0
{ "file_path": "langchain/libs/community/langchain_community/llms/edenai.py", "repo_id": "langchain", "token_count": 4100 }
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"""MongoDB Vector store index. An index that is built on top of an existing vector store. """ import logging import os from importlib.metadata import version from typing import Any, Dict, List, Optional, cast from llama_index.core.bridge.pydantic import PrivateAttr from llama_index.core.schema import BaseNode, Meta...
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-mongodb/llama_index/vector_stores/mongodb/base.py/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-mongodb/llama_index/vector_stores/mongodb/base.py", "repo_id": "llama_index", "token_count": 3586 }
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<jupyter_start><jupyter_text>BabyAGI User GuideThis notebook demonstrates how to implement [BabyAGI](https://github.com/yoheinakajima/babyagi/tree/main) by [Yohei Nakajima](https://twitter.com/yoheinakajima). BabyAGI is an AI agent that can generate and pretend to execute tasks based on a given objective.This guide wil...
langchain/cookbook/baby_agi.ipynb/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/clvp/test_modeling_clvp.py/0
{ "file_path": "transformers/tests/models/clvp/test_modeling_clvp.py", "repo_id": "transformers", "token_count": 11682 }
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from llama_index.core.readers.base import BaseReader from llama_index.readers.discord import DiscordReader def test_class(): names_of_base_classes = [b.__name__ for b in DiscordReader.__mro__] assert BaseReader.__name__ in names_of_base_classes
llama_index/llama-index-integrations/readers/llama-index-readers-discord/tests/test_readers_discord_reader.py/0
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package planparserv2 import "testing" func Test_floatingEqual(t *testing.T) { type args struct { a float64 b float64 } tests := []struct { name string args args want bool }{ { args: args{ a: 1.0, b: 1.0, }, want: true, }, { args: args{ a: 1.0, b: 2.0, }, want: fal...
milvus/internal/parser/planparserv2/floating_comparision_test.go/0
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# coding=utf-8 # Copyright 2022 Google SwitchTransformers Authors and HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0...
transformers/tests/models/switch_transformers/test_modeling_switch_transformers.py/0
{ "file_path": "transformers/tests/models/switch_transformers/test_modeling_switch_transformers.py", "repo_id": "transformers", "token_count": 21272 }
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package model type SegmentMetadataValueType interface { IsSegmentMetadataValueType() } type SegmentMetadataValueStringType struct { Value string } func (s *SegmentMetadataValueStringType) IsSegmentMetadataValueType() {} type SegmentMetadataValueInt64Type struct { Value int64 } func (s *SegmentMetadataValueInt64...
chroma/go/coordinator/internal/model/segment_metadata.go/0
{ "file_path": "chroma/go/coordinator/internal/model/segment_metadata.go", "repo_id": "chroma", "token_count": 439 }
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import { OpenAI, OpenAIEmbeddings } from "@langchain/openai"; import { HNSWLib } from "@langchain/community/vectorstores/hnswlib"; import { RecursiveCharacterTextSplitter } from "langchain/text_splitter"; import * as fs from "fs"; import { VectorStoreToolkit, createVectorStoreAgent, VectorStoreInfo, } from "langc...
langchainjs/examples/src/agents/vectorstore.ts/0
{ "file_path": "langchainjs/examples/src/agents/vectorstore.ts", "repo_id": "langchainjs", "token_count": 418 }
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import datetime import torch import os from loguru import logger from pathlib import Path from safetensors.torch import save_file, load_file, _find_shared_tensors, _is_complete from typing import List, Dict from collections import defaultdict def _remove_duplicate_names( state_dict: Dict[str, torch.Tensor], ...
text-generation-inference/server/text_generation_server/utils/convert.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/utils/convert.py", "repo_id": "text-generation-inference", "token_count": 1769 }
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# Vearch [Vearch](https://github.com/vearch/vearch) is a scalable distributed system for efficient similarity search of deep learning vectors. # Installation and Setup Vearch Python SDK enables vearch to use locally. Vearch python sdk can be installed easily by pip install vearch. # Vectorstore Vearch also can use...
langchain/docs/docs/integrations/providers/vearch.md/0
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import logging from abc import ABC, abstractmethod from typing import Any, Dict, List, Optional, Type import numpy as np from llama_index.core.bridge.pydantic import Field from llama_index.core.schema import BaseNode, MetadataMode, TextNode from llama_index.core.vector_stores.types import ( VectorStore, Vector...
llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-docarray/llama_index/vector_stores/docarray/base.py/0
{ "file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-docarray/llama_index/vector_stores/docarray/base.py", "repo_id": "llama_index", "token_count": 3043 }
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import { z } from "zod"; import { createMetadataTaggerFromZod } from "langchain/document_transformers/openai_functions"; import { ChatOpenAI } from "@langchain/openai"; import { Document } from "@langchain/core/documents"; import { PromptTemplate } from "@langchain/core/prompts"; const taggingChainTemplate = `Extract ...
langchainjs/examples/src/document_transformers/metadata_tagger_custom_prompt.ts/0
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## Appendix B. API Reference In this section, we introduce the RPCs of milvus service. A brief description of the RPCs is listed as follows. | RPC | description | | :---------------------- | -------------------------...
milvus/docs/developer_guides/appendix_b_api_reference.md/0
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from llama_index.finetuning.gradient.base import GradientFinetuneEngine __all__ = ["GradientFinetuneEngine"]
llama_index/llama-index-finetuning/llama_index/finetuning/gradient/__init__.py/0
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# Dev container This project includes a [dev container](https://containers.dev/), which lets you use a container as a full-featured dev environment. You can use the dev container configuration in this folder to build and run the app without needing to install any of its tools locally! You can use it in [GitHub Codesp...
langchain/.devcontainer/README.md/0
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import torch from text_generation_server.utils.tokens import ( StopSequenceCriteria, StoppingCriteria, FinishReason, batch_top_tokens, ) def test_stop_sequence_criteria(): criteria = StopSequenceCriteria("/test;") assert not criteria("/") assert not criteria("/test") assert criteria("...
text-generation-inference/server/tests/utils/test_tokens.py/0
{ "file_path": "text-generation-inference/server/tests/utils/test_tokens.py", "repo_id": "text-generation-inference", "token_count": 1427 }
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from llama_index.readers.airbyte_typeform.base import AirbyteTypeformReader __all__ = ["AirbyteTypeformReader"]
llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-typeform/llama_index/readers/airbyte_typeform/__init__.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-typeform/llama_index/readers/airbyte_typeform/__init__.py", "repo_id": "llama_index", "token_count": 36 }
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"""Obsidian reader class. Pass in the path to an Obsidian vault and it will parse all markdown files into a List of Documents, with each Document containing text from under an Obsidian header. """ import os from pathlib import Path from typing import Any, List from llama_index.legacy.readers.base import BaseReader ...
llama_index/llama-index-legacy/llama_index/legacy/readers/obsidian.py/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/obsidian.py", "repo_id": "llama_index", "token_count": 505 }
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// Copyright 2019 PingCAP, Inc. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to i...
milvus/pkg/log/global.go/0
{ "file_path": "milvus/pkg/log/global.go", "repo_id": "milvus", "token_count": 2024 }
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import glob import importlib from pathlib import Path def test_importable_all() -> None: for path in glob.glob("../core/langchain_core/*"): relative_path = Path(path).parts[-1] if relative_path.endswith(".typed"): continue module_name = relative_path.split(".")[0] modul...
langchain/libs/core/tests/unit_tests/test_imports.py/0
{ "file_path": "langchain/libs/core/tests/unit_tests/test_imports.py", "repo_id": "langchain", "token_count": 213 }
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from typing import Any, Dict, List, Optional, Union from langchain_core.callbacks import CallbackManagerForLLMRun from langchain_core.language_models.llms import BaseLLM from langchain_core.outputs import Generation, LLMResult from langchain_core.pydantic_v1 import Field, root_validator class CTranslate2(BaseLLM): ...
langchain/libs/community/langchain_community/llms/ctranslate2.py/0
{ "file_path": "langchain/libs/community/langchain_community/llms/ctranslate2.py", "repo_id": "langchain", "token_count": 1672 }
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"""Serialization and deserialization.""" from langchain_core.load.dump import dumpd, dumps from langchain_core.load.load import load, loads __all__ = [ "dumpd", "dumps", "load", "loads", ]
langchain/libs/langchain/langchain/load/__init__.py/0
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<jupyter_start><jupyter_text>Knowledge Graph Query EngineCreating a Knowledge Graph usually involves specialized and complex tasks. However, by utilizing the Llama Index (LLM), the KnowledgeGraphIndex, and the GraphStore, we can facilitate the creation of a relatively effective Knowledge Graph from any data source supp...
llama_index/docs/examples/query_engine/knowledge_graph_query_engine.ipynb/0
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# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/src/transformers/models/marian/tokenization_marian.py/0
{ "file_path": "transformers/src/transformers/models/marian/tokenization_marian.py", "repo_id": "transformers", "token_count": 7701 }
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import { QdrantVectorStore } from "@langchain/community/vectorstores/qdrant"; import { OpenAIEmbeddings } from "@langchain/openai"; // text sample from Godel, Escher, Bach const vectorStore = await QdrantVectorStore.fromTexts( [ `Tortoise: Labyrinth? Labyrinth? Could it Are we in the notorious Little Harmonic Lab...
langchainjs/examples/src/indexes/vector_stores/qdrant/fromTexts.ts/0
{ "file_path": "langchainjs/examples/src/indexes/vector_stores/qdrant/fromTexts.ts", "repo_id": "langchainjs", "token_count": 462 }
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[ { "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 1276, "logprob": null, "text": "What" }, { "id": 310, "logprob": -0.83984375, "text": " is...
text-generation-inference/integration-tests/models/__snapshots__/test_mamba/test_mamba_load.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mamba/test_mamba_load.json", "repo_id": "text-generation-inference", "token_count": 5458 }
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import getopt import json import os # import numpy as np import sys from collections import OrderedDict import datasets import numpy as np import torch from modeling_frcnn import GeneralizedRCNN from processing_image import Preprocess from utils import Config """ USAGE: ``python extracting_data.py -i <img_dir> -o ...
transformers/examples/research_projects/lxmert/extracting_data.py/0
{ "file_path": "transformers/examples/research_projects/lxmert/extracting_data.py", "repo_id": "transformers", "token_count": 2528 }
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"""Main module for DocstringWalker loader for Llama Hub.""" import ast import logging import os from typing import List from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document TYPES_TO_PROCESS = {ast.FunctionDef, ast.ClassDef} log = logging.getLogger(__name__) class Docst...
llama_index/llama-index-integrations/readers/llama-index-readers-docstring-walker/llama_index/readers/docstring_walker/base.py/0
{ "file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-docstring-walker/llama_index/readers/docstring_walker/base.py", "repo_id": "llama_index", "token_count": 3321 }
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import { BaseLLM } from "@langchain/core/language_models/llms"; import { Generation, GenerationChunk, LLMResult, } from "@langchain/core/outputs"; import type { BaseLanguageModelCallOptions } from "@langchain/core/language_models/base"; import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";...
langchainjs/libs/langchain-community/src/llms/googlevertexai/common.ts/0
{ "file_path": "langchainjs/libs/langchain-community/src/llms/googlevertexai/common.ts", "repo_id": "langchainjs", "token_count": 2207 }
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package typeutil import ( "sync" "go.uber.org/atomic" ) // MapEqual returns true if the two map contain the same keys and values func MapEqual(left, right map[int64]int64) bool { if len(left) != len(right) { return false } for k, v := range left { if v2, ok := right[k]; !ok || v != v2 { return false }...
milvus/pkg/util/typeutil/map.go/0
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from llama_index.legacy.node_parser.relational.hierarchical import ( HierarchicalNodeParser, ) from llama_index.legacy.node_parser.relational.markdown_element import ( MarkdownElementNodeParser, ) from llama_index.legacy.node_parser.relational.unstructured_element import ( UnstructuredElementNodeParser, ) ...
llama_index/llama-index-legacy/llama_index/legacy/node_parser/relational/__init__.py/0
{ "file_path": "llama_index/llama-index-legacy/llama_index/legacy/node_parser/relational/__init__.py", "repo_id": "llama_index", "token_count": 151 }
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<jupyter_start><jupyter_text>Stable Conceptualizer - Stable Diffusion using learned conceptsThe Stable Conceptualizer enables you to use pre-learned concepts on Stable Diffusion via textual-inversion using 🤗 Hugging Face [🧨 Diffusers library](https://github.com/huggingface/diffusers). Navigate the [library of pre-lea...
notebooks/diffusers/stable_conceptualizer_inference.ipynb/0
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import { Document, type DocumentInterface } from "@langchain/core/documents"; import { RemoteRetriever, RemoteRetrieverValues, RemoteRetrieverParams, } from "./remote/base.js"; export interface VespaRetrieverParams extends RemoteRetrieverParams { /** * The body of the query to send to Vespa */ query_bo...
langchainjs/libs/langchain-community/src/retrievers/vespa.ts/0
{ "file_path": "langchainjs/libs/langchain-community/src/retrievers/vespa.ts", "repo_id": "langchainjs", "token_count": 884 }
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package observers import ( "context" "sync" "testing" "time" "github.com/stretchr/testify/suite" "github.com/milvus-io/milvus/pkg/util/paramtable" "github.com/milvus-io/milvus/pkg/util/typeutil" ) type taskDispatcherSuite struct { suite.Suite } func (s *taskDispatcherSuite) SetupSuite() { paramtable.Get()...
milvus/internal/querycoordv2/observers/task_dispatcher_test.go/0
{ "file_path": "milvus/internal/querycoordv2/observers/task_dispatcher_test.go", "repo_id": "milvus", "token_count": 386 }
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"""Read Arxiv Papers.""" import hashlib import logging import os from typing import List, Optional, Tuple from llama_index.core.readers import SimpleDirectoryReader from llama_index.core.readers.base import BaseReader from llama_index.core.schema import Document class ArxivReader(BaseReader): """Arxiv Reader. ...
llama_index/llama-index-integrations/readers/llama-index-readers-papers/llama_index/readers/papers/arxiv/base.py/0
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# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/utils/test_versions_utils.py/0
{ "file_path": "transformers/tests/utils/test_versions_utils.py", "repo_id": "transformers", "token_count": 1539 }
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import { ChatAnthropic } from "@langchain/anthropic"; const model = new ChatAnthropic({ temperature: 0.9, anthropicApiKey: "YOUR-API-KEY", // In Node.js defaults to process.env.ANTHROPIC_API_KEY maxTokensToSample: 1024, });
langchainjs/examples/src/models/chat/integration_anthropic_legacy.ts/0
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# coding=utf-8 # Copyright 2022 KAIST and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # ...
transformers/src/transformers/models/glpn/configuration_glpn.py/0
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package optimizers import ( "context" "testing" "github.com/golang/protobuf/proto" "github.com/stretchr/testify/mock" "github.com/stretchr/testify/suite" "github.com/milvus-io/milvus/internal/proto/internalpb" "github.com/milvus-io/milvus/internal/proto/planpb" "github.com/milvus-io/milvus/internal/proto/que...
milvus/internal/querynodev2/optimizers/query_hook_test.go/0
{ "file_path": "milvus/internal/querynodev2/optimizers/query_hook_test.go", "repo_id": "milvus", "token_count": 2102 }
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/pipelines/controlnet/test_controlnet.py/0
{ "file_path": "diffusers/tests/pipelines/controlnet/test_controlnet.py", "repo_id": "diffusers", "token_count": 19057 }
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ko/perf_train_cpu_many.md/0
{ "file_path": "transformers/docs/source/ko/perf_train_cpu_many.md", "repo_id": "transformers", "token_count": 4046 }
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""" Squeeze-and-Excitation Channel Attention An SE implementation originally based on PyTorch SE-Net impl. Has since evolved with additional functionality / configuration. Paper: `Squeeze-and-Excitation Networks` - https://arxiv.org/abs/1709.01507 Also included is Effective Squeeze-Excitation (ESE). Paper: `CenterMa...
pytorch-image-models/timm/layers/squeeze_excite.py/0
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