text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
from langchain_community.tools.ifttt import IFTTTWebhook
__all__ = ["IFTTTWebhook"]
| langchain/libs/langchain/langchain/tools/ifttt.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/ifttt.py",
"repo_id": "langchain",
"token_count": 31
} | 559 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/querynodev2/segments/segment_loader.go/0 | {
"file_path": "milvus/internal/querynodev2/segments/segment_loader.go",
"repo_id": "milvus",
"token_count": 18142
} | 1,856 |
from langchain_community.chat_models import ChatOpenAI
from langchain_core.load import load
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnables import RunnablePassthrough
from prop... | langchain/templates/propositional-retrieval/propositional_retrieval/chain.py/0 | {
"file_path": "langchain/templates/propositional-retrieval/propositional_retrieval/chain.py",
"repo_id": "langchain",
"token_count": 739
} | 656 |
"""Agent for working with pandas objects."""
import warnings
from typing import Any, Dict, List, Literal, Optional, Sequence, Union
from langchain.agents import AgentType, create_openai_tools_agent, create_react_agent
from langchain.agents.agent import (
AgentExecutor,
BaseMultiActionAgent,
BaseSingleActio... | langchain/libs/experimental/langchain_experimental/agents/agent_toolkits/pandas/base.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/agents/agent_toolkits/pandas/base.py",
"repo_id": "langchain",
"token_count": 4662
} | 435 |
# Conversation buffer window memory
`ConversationBufferWindowMemory` keeps a list of the interactions of the conversation over time. It only uses the last K interactions. This can be useful for keeping a sliding window of the most recent interactions, so the buffer does not get too large
Let's first explore the basic... | langchainjs/docs/core_docs/docs/modules/memory/types/buffer_window.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/memory/types/buffer_window.mdx",
"repo_id": "langchainjs",
"token_count": 362
} | 814 |
---
sidebar_position: 4
---
# LLMs
Large Language Models (LLMs) are a core component of LangChain.
LangChain does not serve its own LLMs, but rather provides a standard interface for interacting with many different LLMs. To be specific, this interface is one that takes as input a string and returns a string.
There ... | langchain/docs/docs/modules/model_io/llms/index.mdx/0 | {
"file_path": "langchain/docs/docs/modules/model_io/llms/index.mdx",
"repo_id": "langchain",
"token_count": 317
} | 206 |
# Starter Tutorial (Local Models)
```{tip}
Make sure you've followed the [custom installation](installation.md) steps first.
```
This is our famous "5 lines of code" starter example with local LLM and embedding models. We will use `BAAI/bge-m3` as our embedding model and `Mistral-7B` served through `Ollama` as our LL... | llama_index/docs/getting_started/starter_example_local.md/0 | {
"file_path": "llama_index/docs/getting_started/starter_example_local.md",
"repo_id": "llama_index",
"token_count": 904
} | 1,089 |
python_sources()
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/llama_index/embeddings/bedrock/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-bedrock/llama_index/embeddings/bedrock/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,354 |
# 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/deepfloyd_if/test_if_superresolution.py/0 | {
"file_path": "diffusers/tests/pipelines/deepfloyd_if/test_if_superresolution.py",
"repo_id": "diffusers",
"token_count": 1925
} | 270 |
python_tests(
interpreter_constraints=["==3.9.*", "==3.10.*"],
)
| llama_index/llama-index-integrations/readers/llama-index-readers-pandas-ai/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-pandas-ai/tests/BUILD",
"repo_id": "llama_index",
"token_count": 29
} | 1,412 |
<jupyter_start><jupyter_text>Finetune EmbeddingsIn this notebook, we show users how to finetune their own embedding models.We go through three main sections:1. Preparing the data (our `generate_qa_embedding_pairs` function makes this easy)2. Finetuning the model (using our `SentenceTransformersFinetuneEngine`)3. Evalua... | llama_index/docs/examples/finetuning/embeddings/finetune_embedding.ipynb/0 | {
"file_path": "llama_index/docs/examples/finetuning/embeddings/finetune_embedding.ipynb",
"repo_id": "llama_index",
"token_count": 3214
} | 1,119 |
python_sources()
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-google/llama_index/embeddings/google/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-google/llama_index/embeddings/google/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,230 |
from csv_agent.agent import agent_executor
__all__ = ["agent_executor"]
| langchain/templates/csv-agent/csv_agent/__init__.py/0 | {
"file_path": "langchain/templates/csv-agent/csv_agent/__init__.py",
"repo_id": "langchain",
"token_count": 25
} | 670 |
poetry_requirements(
name="poetry",
)
python_requirements(
name="reqs",
)
| llama_index/llama-index-integrations/tools/llama-index-tools-tavily-research/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-tavily-research/BUILD",
"repo_id": "llama_index",
"token_count": 36
} | 1,498 |
# StarRocks
>[StarRocks](https://www.starrocks.io/) is a High-Performance Analytical Database.
`StarRocks` is a next-gen sub-second MPP database for full analytics scenarios, including multi-dimensional analytics, real-time analytics and ad-hoc query.
>Usually `StarRocks` is categorized into OLAP, and it has showed e... | langchain/docs/docs/integrations/providers/starrocks.mdx/0 | {
"file_path": "langchain/docs/docs/integrations/providers/starrocks.mdx",
"repo_id": "langchain",
"token_count": 210
} | 153 |
<jupyter_start><jupyter_text>ClientDemo of a client interacting with a configurable retriever (see server code) You can interact with this via API directly<jupyter_code>import requests
inputs = {"input": "cat"}
response = requests.post("http://localhost:8000/invoke", json=inputs)
response.json()<jupyter_output><empty... | langserve/examples/configurable_retrieval/client.ipynb/0 | {
"file_path": "langserve/examples/configurable_retrieval/client.ipynb",
"repo_id": "langserve",
"token_count": 290
} | 1,042 |
import logging
import os
from typing import Any, Dict, Iterator, List, Mapping, Optional, Union
from ibm_watsonx_ai.foundation_models import ModelInference # type: ignore
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import BaseLLM
from langchain_core.outputs i... | langchain/libs/partners/ibm/langchain_ibm/llms.py/0 | {
"file_path": "langchain/libs/partners/ibm/langchain_ibm/llms.py",
"repo_id": "langchain",
"token_count": 6781
} | 647 |
import * as uuid from "uuid";
import type { ChainValues } from "../utils/types.js";
import type { BaseMessage } from "../messages/index.js";
import type { AgentAction, AgentFinish } from "../agents.js";
import type {
ChatGenerationChunk,
GenerationChunk,
LLMResult,
} from "../outputs.js";
import {
Serializable,... | langchainjs/langchain-core/src/callbacks/base.ts/0 | {
"file_path": "langchainjs/langchain-core/src/callbacks/base.ts",
"repo_id": "langchainjs",
"token_count": 3435
} | 830 |
from __future__ import annotations
from typing import (
TYPE_CHECKING,
List,
Optional,
)
if TYPE_CHECKING:
import rdflib
prefixes = {
"owl": """PREFIX owl: <http://www.w3.org/2002/07/owl#>\n""",
"rdf": """PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>\n""",
"rdfs": """PREFIX rd... | langchain/libs/community/langchain_community/graphs/rdf_graph.py/0 | {
"file_path": "langchain/libs/community/langchain_community/graphs/rdf_graph.py",
"repo_id": "langchain",
"token_count": 4789
} | 282 |
from langchain_core.runnables.passthrough import (
RunnableAssign,
RunnablePassthrough,
aidentity,
identity,
)
__all__ = ["aidentity", "identity", "RunnablePassthrough", "RunnableAssign"]
| langchain/libs/langchain/langchain/schema/runnable/passthrough.py/0 | {
"file_path": "langchain/libs/langchain/langchain/schema/runnable/passthrough.py",
"repo_id": "langchain",
"token_count": 85
} | 578 |
python_tests(
interpreter_constraints=["==3.9.*", "==3.10.*"],
)
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-google/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-google/tests/BUILD",
"repo_id": "llama_index",
"token_count": 29
} | 1,259 |
python_tests()
| llama_index/llama-index-integrations/readers/llama-index-readers-zep/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zep/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,480 |
# flake8: noqa
"""Test Llama.cpp wrapper."""
import os
from typing import Generator
from urllib.request import urlretrieve
import pytest
from langchain_community.llms import LlamaCpp
from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
def get_model() -> str:
"""Download model. f
... | langchain/libs/community/tests/integration_tests/llms/test_llamacpp.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_llamacpp.py",
"repo_id": "langchain",
"token_count": 1272
} | 357 |
"""
This tool allows agents to interact with the atlassian-python-api library
and operate on a Jira instance. For more information on the
atlassian-python-api library, see https://atlassian-python-api.readthedocs.io/jira.html
To use this tool, you must first set as environment variables:
JIRA_API_TOKEN
JIRA_US... | langchain/libs/community/langchain_community/tools/jira/tool.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/jira/tool.py",
"repo_id": "langchain",
"token_count": 461
} | 303 |
<script lang="ts">
import { marked } from "marked";
import markedKatex from "marked-katex-extension";
import type { Message } from "$lib/types/Message";
import { afterUpdate, createEventDispatcher, tick } from "svelte";
import { deepestChild } from "$lib/utils/deepestChild";
import { page } from "$app/stores";
... | chat-ui/src/lib/components/chat/ChatMessage.svelte/0 | {
"file_path": "chat-ui/src/lib/components/chat/ChatMessage.svelte",
"repo_id": "chat-ui",
"token_count": 6624
} | 88 |
# Copyright 2020 The HuggingFace Authors.
#
# 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... | datasets/src/datasets/formatting/tf_formatter.py/0 | {
"file_path": "datasets/src/datasets/formatting/tf_formatter.py",
"repo_id": "datasets",
"token_count": 1885
} | 131 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
logging.b... | transformers/examples/research_projects/rag/_test_finetune_rag.py/0 | {
"file_path": "transformers/examples/research_projects/rag/_test_finetune_rag.py",
"repo_id": "transformers",
"token_count": 1994
} | 572 |
#!/usr/bin/env bash
# Licensed to the LF AI & Data foundation under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you... | milvus/scripts/install_deps_embd.sh/0 | {
"file_path": "milvus/scripts/install_deps_embd.sh",
"repo_id": "milvus",
"token_count": 2017
} | 1,858 |
# Xception
**Xception** is a convolutional neural network architecture that relies solely on [depthwise separable convolution layers](https://paperswithcode.com/method/depthwise-separable-convolution).
The weights from this model were ported from [Tensorflow/Models](https://github.com/tensorflow/models).
{% include ... | pytorch-image-models/docs/models/.templates/models/xception.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/xception.md",
"repo_id": "pytorch-image-models",
"token_count": 1874
} | 321 |
from langchain_community.tools.playwright.current_page import CurrentWebPageTool
__all__ = ["CurrentWebPageTool"]
| langchain/libs/langchain/langchain/tools/playwright/current_page.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/playwright/current_page.py",
"repo_id": "langchain",
"token_count": 32
} | 595 |
<jupyter_start><jupyter_text>BeamCalls the Beam API wrapper to deploy and make subsequent calls to an instance of the gpt2 LLM in a cloud deployment. Requires installation of the Beam library and registration of Beam Client ID and Client Secret. By calling the wrapper an instance of the model is created and run, with r... | langchain/docs/docs/integrations/llms/beam.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/beam.ipynb",
"repo_id": "langchain",
"token_count": 709
} | 116 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "vectorstores/lancedb",
});
export * from "@langchain/community/vectorstores/lancedb";
| langchainjs/langchain/src/vectorstores/lancedb.ts/0 | {
"file_path": "langchainjs/langchain/src/vectorstores/lancedb.ts",
"repo_id": "langchainjs",
"token_count": 74
} | 936 |
"""Test functionality related to ngram overlap based selector."""
import pytest
from langchain_core.prompts import PromptTemplate
from langchain.prompts.example_selector.ngram_overlap import (
NGramOverlapExampleSelector,
ngram_overlap_score,
)
EXAMPLES = [
{"input": "See Spot run.", "output": "foo1"},
... | langchain/libs/langchain/tests/integration_tests/prompts/test_ngram_overlap_example_selector.py/0 | {
"file_path": "langchain/libs/langchain/tests/integration_tests/prompts/test_ngram_overlap_example_selector.py",
"repo_id": "langchain",
"token_count": 962
} | 617 |
python_sources()
| llama_index/llama-index-core/llama_index/core/node_parser/relational/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/node_parser/relational/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,191 |
import { test, expect } from "@jest/globals";
import { AgentAction, AgentFinish } from "@langchain/core/agents";
import { ChatConversationalAgentOutputParser } from "../chat_convo/outputParser.js";
test("Can parse JSON with text in front of it", async () => {
const testCases = [
{
input: `Based on the info... | langchainjs/langchain/src/agents/tests/chat_convo_output_parser.test.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/tests/chat_convo_output_parser.test.ts",
"repo_id": "langchainjs",
"token_count": 2793
} | 870 |
// 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/core/unittest/test_local_chunk_manager.cpp/0 | {
"file_path": "milvus/internal/core/unittest/test_local_chunk_manager.cpp",
"repo_id": "milvus",
"token_count": 3471
} | 1,903 |
# Fake LLM
LangChain provides a fake LLM chat model for testing purposes. This allows you to mock out calls to the LLM and and simulate what would happen if the LLM responded in a certain way.
## Usage
import CodeBlock from "@theme/CodeBlock";
import FakeListChatExample from "@examples/models/chat/integration_fake.t... | langchainjs/docs/core_docs/docs/integrations/chat/fake.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/chat/fake.mdx",
"repo_id": "langchainjs",
"token_count": 107
} | 722 |
import {
ChatPromptTemplate,
HumanMessagePromptTemplate,
PromptTemplate,
SystemMessagePromptTemplate,
} from "@langchain/core/prompts";
export const run = async () => {
const template = "What is a good name for a company that makes {product}?";
const promptA = new PromptTemplate({ template, inputVariables:... | langchainjs/examples/src/prompts/prompt_value.ts/0 | {
"file_path": "langchainjs/examples/src/prompts/prompt_value.ts",
"repo_id": "langchainjs",
"token_count": 738
} | 844 |
"""
**Utility functions** for LangChain.
"""
| langchain/libs/community/langchain_community/utils/__init__.py/0 | {
"file_path": "langchain/libs/community/langchain_community/utils/__init__.py",
"repo_id": "langchain",
"token_count": 14
} | 321 |
<jupyter_start><jupyter_text>vLLM[vLLM](https://vllm.readthedocs.io/en/latest/index.html) is a fast and easy-to-use library for LLM inference and serving, offering:* State-of-the-art serving throughput * Efficient management of attention key and value memory with PagedAttention* Continuous batching of incoming requests... | langchain/docs/docs/integrations/llms/vllm.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/llms/vllm.ipynb",
"repo_id": "langchain",
"token_count": 1140
} | 120 |
# coding=utf-8
# Copyright 2023 The Pop2Piano Authors and The 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
#
# Unl... | transformers/src/transformers/models/pop2piano/tokenization_pop2piano.py/0 | {
"file_path": "transformers/src/transformers/models/pop2piano/tokenization_pop2piano.py",
"repo_id": "transformers",
"token_count": 14434
} | 657 |
python_tests(
name="tests",
skip_tests=True,
)
| llama_index/llama-index-legacy/tests/indices/managed/BUILD/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/managed/BUILD",
"repo_id": "llama_index",
"token_count": 25
} | 1,552 |
[build-system]
build-backend = "poetry.core.masonry.api"
requires = ["poetry-core"]
[tool.codespell]
check-filenames = true
check-hidden = true
skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
[tool.llamahub]
classes = ["SalesforceToolSpec"]
contains_example = false
import_path = "llama_index.tools.salesforce... | llama_index/llama-index-integrations/tools/llama-index-tools-salesforce/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-salesforce/pyproject.toml",
"repo_id": "llama_index",
"token_count": 669
} | 1,580 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/pkg/eventlog/global.go/0 | {
"file_path": "milvus/pkg/eventlog/global.go",
"repo_id": "milvus",
"token_count": 833
} | 2,087 |
from typing import TYPE_CHECKING
from langchain_community.document_loaders.parsers.language.tree_sitter_segmenter import ( # noqa: E501
TreeSitterSegmenter,
)
if TYPE_CHECKING:
from tree_sitter import Language
CHUNK_QUERY = """
[
(function_declaration) @function
(class_declaration) @cla... | langchain/libs/community/langchain_community/document_loaders/parsers/language/typescript.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/language/typescript.py",
"repo_id": "langchain",
"token_count": 313
} | 246 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/pkg/util/typeutil/float_util.go/0 | {
"file_path": "milvus/pkg/util/typeutil/float_util.go",
"repo_id": "milvus",
"token_count": 424
} | 1,925 |
# coding=utf-8
# Copyright 2022 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/glpn/test_modeling_glpn.py/0 | {
"file_path": "transformers/tests/models/glpn/test_modeling_glpn.py",
"repo_id": "transformers",
"token_count": 6153
} | 726 |
"""Tool for the Google search API."""
from typing import Optional, Type
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import BaseTool
from langchain_community.utilities.google_places_api import GooglePlacesAPIWrapper
... | langchain/libs/community/langchain_community/tools/google_places/tool.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/google_places/tool.py",
"repo_id": "langchain",
"token_count": 394
} | 305 |
# CSP-ResNet
**CSPResNet** is a convolutional neural network where we apply the Cross Stage Partial Network (CSPNet) approach to [ResNet](https://paperswithcode.com/method/resnet). The CSPNet partitions the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of a ... | pytorch-image-models/docs/models/.templates/models/csp-resnet.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/csp-resnet.md",
"repo_id": "pytorch-image-models",
"token_count": 897
} | 345 |
import path from "node:path";
import fs from "node:fs/promises";
import {
BaseCache,
getCacheKey,
serializeGeneration,
deserializeStoredGeneration,
} from "@langchain/core/caches";
import { Generation } from "@langchain/core/outputs";
/**
* A cache that uses the local filesystem as the backing store.
* This... | langchainjs/langchain/src/cache/file_system.ts/0 | {
"file_path": "langchainjs/langchain/src/cache/file_system.ts",
"repo_id": "langchainjs",
"token_count": 809
} | 857 |
from langchain_community.vectorstores.dashvector import DashVector
__all__ = ["DashVector"]
| langchain/libs/langchain/langchain/vectorstores/dashvector.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/dashvector.py",
"repo_id": "langchain",
"token_count": 25
} | 574 |
# In Memory Store
This example demonstrates how to setup chat history storage using the `InMemoryStore` KV store integration.
## Usage
The `InMemoryStore` allows for a generic type to be assigned to the values in the store.
We'll assign type `BaseMessage` as the type of our values, keeping with the theme of a chat h... | langchainjs/docs/core_docs/docs/integrations/stores/in_memory.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/stores/in_memory.mdx",
"repo_id": "langchainjs",
"token_count": 129
} | 722 |
<jupyter_start><jupyter_text>ThirdAI NeuralDB>[NeuralDB](https://www.thirdai.com/neuraldb-enterprise/) is a CPU-friendly and fine-tunable vector store developed by [ThirdAI](https://www.thirdai.com/). InitializationThere are three initialization methods:- From Scratch: Basic model- From Bazaar: Download a pretrained ba... | langchain/docs/docs/integrations/vectorstores/thirdai_neuraldb.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/thirdai_neuraldb.ipynb",
"repo_id": "langchain",
"token_count": 1365
} | 186 |
# coding=utf-8
# Copyright 2018 The 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
#
# Unless required by applicable... | transformers/src/transformers/models/deprecated/transfo_xl/convert_transfo_xl_original_tf_checkpoint_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/deprecated/transfo_xl/convert_transfo_xl_original_tf_checkpoint_to_pytorch.py",
"repo_id": "transformers",
"token_count": 1991
} | 591 |
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import type { DocumentInterface } from "@langchain/core/documents";
import { cosineSimilarity } from "@langchain/core/utils/math";
import { BaseDocumentCompressor } from "./index.js";
/**
* Interface for the parameters of the `EmbeddingsFilter` cl... | langchainjs/langchain/src/retrievers/document_compressors/embeddings_filter.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/document_compressors/embeddings_filter.ts",
"repo_id": "langchainjs",
"token_count": 1006
} | 980 |
# flake8: noqa
"""Test rwkv wrapper."""
import os
from urllib.request import urlretrieve
from langchain_community.llms import RWKV
import warnings
import pytest
def _download_model() -> str:
"""Download model.
From https://huggingface.co/BlinkDL/rwkv-4-pile-169m/resolve/main/RWKV-4-Pile-169M-20220807-8023.pt... | langchain/libs/community/tests/integration_tests/llms/test_rwkv.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_rwkv.py",
"repo_id": "langchain",
"token_count": 486
} | 341 |
FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
LABEL maintainer="Hugging Face"
LABEL repository="transformers"
RUN apt update && \
apt install -y bash \
build-essential \
git \
curl \
ca-certificates \
python3 \
... | transformers/docker/transformers-gpu/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-gpu/Dockerfile",
"repo_id": "transformers",
"token_count": 397
} | 461 |
babel.config.js
jest.config.js
.eslintrc.js
| langchainjs/.prettierignore/0 | {
"file_path": "langchainjs/.prettierignore",
"repo_id": "langchainjs",
"token_count": 22
} | 689 |
# coding=utf-8
# Copyright 2021 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/tapas/test_modeling_tf_tapas.py/0 | {
"file_path": "transformers/tests/models/tapas/test_modeling_tf_tapas.py",
"repo_id": "transformers",
"token_count": 21105
} | 845 |
import logging
import os
from pathlib import Path
from time import sleep
from typing import Callable, List, Optional, Union
import numpy as np
import tensorflow as tf
from huggingface_hub import Repository, create_repo
from packaging.version import parse
from . import IntervalStrategy, PreTrainedTokenizerBase
from .m... | transformers/src/transformers/keras_callbacks.py/0 | {
"file_path": "transformers/src/transformers/keras_callbacks.py",
"repo_id": "transformers",
"token_count": 8732
} | 563 |
python_tests()
| llama_index/llama-index-integrations/readers/llama-index-readers-steamship/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-steamship/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,530 |
"""Test Confident."""
def test_confident_deepeval() -> None:
"""Test valid call to Beam."""
from deepeval.metrics.answer_relevancy import AnswerRelevancy
from langchain_community.callbacks.confident_callback import DeepEvalCallbackHandler
from langchain_community.llms import OpenAI
answer_releva... | langchain/libs/community/tests/integration_tests/llms/test_confident.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_confident.py",
"repo_id": "langchain",
"token_count": 328
} | 355 |
// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use th... | milvus/internal/distributed/proxy/service.go/0 | {
"file_path": "milvus/internal/distributed/proxy/service.go",
"repo_id": "milvus",
"token_count": 16250
} | 1,987 |
from datetime import datetime
from typing import Dict, Tuple, Union
from langchain.chains.query_constructor.ir import (
Comparator,
Comparison,
Operation,
Operator,
StructuredQuery,
Visitor,
)
class WeaviateTranslator(Visitor):
"""Translate `Weaviate` internal query language elements to v... | langchain/libs/langchain/langchain/retrievers/self_query/weaviate.py/0 | {
"file_path": "langchain/libs/langchain/langchain/retrievers/self_query/weaviate.py",
"repo_id": "langchain",
"token_count": 1192
} | 539 |
from langchain_community.embeddings import FakeEmbeddings
from langchain_community.retrievers.knn import KNNRetriever
class TestKNNRetriever:
def test_from_texts(self) -> None:
input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
knn_retriever = KNNRetriever.from_texts(
... | langchain/libs/community/tests/unit_tests/retrievers/test_knn.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/retrievers/test_knn.py",
"repo_id": "langchain",
"token_count": 184
} | 411 |
/* eslint-disable no-process-env */
/* eslint-disable @typescript-eslint/no-non-null-assertion */
import { beforeEach, describe, expect, test } from "@jest/globals";
import { ChromaClient } from "chromadb";
import { faker } from "@faker-js/faker";
import * as uuid from "uuid";
import { Document } from "@langchain/core/... | langchainjs/libs/langchain-community/src/vectorstores/tests/chroma.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/tests/chroma.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1692
} | 969 |
<!--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 to... | transformers/docs/source/en/peft.md/0 | {
"file_path": "transformers/docs/source/en/peft.md",
"repo_id": "transformers",
"token_count": 2640
} | 525 |
<jupyter_start><jupyter_text>Github Issue Analysis Setup To use the github repo issue loader, you need to set your github token in the environment. See [here](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens) for how to get a github token. See [llama... | llama_index/docs/examples/usecases/github_issue_analysis.ipynb/0 | {
"file_path": "llama_index/docs/examples/usecases/github_issue_analysis.ipynb",
"repo_id": "llama_index",
"token_count": 1392
} | 1,087 |
import os
from langchain.retrievers.multi_query import MultiQueryRetriever
from langchain_community.chat_models import ChatOpenAI
from langchain_community.vectorstores import Vectara
from langchain_core.output_parsers import StrOutputParser
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnables... | langchain/templates/rag-vectara-multiquery/rag_vectara_multiquery/chain.py/0 | {
"file_path": "langchain/templates/rag-vectara-multiquery/rag_vectara_multiquery/chain.py",
"repo_id": "langchain",
"token_count": 761
} | 750 |
import {
GenerativeModel,
GoogleGenerativeAI as GenerativeAI,
} from "@google/generative-ai";
import type { SafetySetting } from "@google/generative-ai";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { BaseMessage } from "@langchain/core/messages";
import { ChatGenerationChunk... | langchainjs/libs/langchain-google-genai/src/chat_models.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-genai/src/chat_models.ts",
"repo_id": "langchainjs",
"token_count": 3573
} | 1,100 |
from langchain.pydantic_v1 import BaseModel
from langchain_core.runnables import RunnablePassthrough
from sql_research_assistant.search.web import chain as search_chain
from sql_research_assistant.writer import chain as writer_chain
chain_notypes = (
RunnablePassthrough().assign(research_summary=search_chain) | w... | langchain/templates/sql-research-assistant/sql_research_assistant/chain.py/0 | {
"file_path": "langchain/templates/sql-research-assistant/sql_research_assistant/chain.py",
"repo_id": "langchain",
"token_count": 197
} | 757 |
import { test } from "@jest/globals";
import { SortXYZBlockchainLoader } from "../web/sort_xyz_blockchain.js";
const SORT_XYZ_DEMO_API_KEY = "dd46a0ae-5a1a-4c6f-8328-46618c4a73d4";
const contractAddress =
"0x887F3909C14DAbd9e9510128cA6cBb448E932d7f".toLowerCase();
test.skip("Test Blockchain NFT Metadata Loader", as... | langchainjs/langchain/src/document_loaders/tests/sort_xyz_blockchain.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/tests/sort_xyz_blockchain.int.test.ts",
"repo_id": "langchainjs",
"token_count": 518
} | 869 |
#!/bin/bash
export CUDA_VISIBLE_DEVICES=0
PATH_TO_DATA=/h/xinji/projects/GLUE
MODEL_TYPE=bert # bert or roberta
MODEL_SIZE=base # base or large
DATASET=MRPC # SST-2, MRPC, RTE, QNLI, QQP, or MNLI
MODEL_NAME=${MODEL_TYPE}-${MODEL_SIZE}
EPOCHS=10
if [ $MODEL_TYPE = 'bert' ]
then
EPOCHS=3
MODEL_NAME=${MODEL_NAME... | transformers/examples/research_projects/deebert/train_deebert.sh/0 | {
"file_path": "transformers/examples/research_projects/deebert/train_deebert.sh",
"repo_id": "transformers",
"token_count": 417
} | 573 |
from langchain_community.vectorstores.cassandra import CVST, Cassandra
__all__ = ["CVST", "Cassandra"]
| langchain/libs/langchain/langchain/vectorstores/cassandra.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/cassandra.py",
"repo_id": "langchain",
"token_count": 32
} | 601 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def tokenize(example):
output = {}
output["input_ids"] = tokenizer(example["content"], truncation=False)["input_ids"]
output["ratio... | transformers/examples/research_projects/codeparrot/scripts/pretokenizing.py/0 | {
"file_path": "transformers/examples/research_projects/codeparrot/scripts/pretokenizing.py",
"repo_id": "transformers",
"token_count": 527
} | 557 |
"""Experiment with different models."""
from __future__ import annotations
from typing import List, Optional, Sequence
from langchain_core.language_models.llms import BaseLLM
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.utils.input import get_color_mapping, print_text
from langchain.... | langchain/libs/langchain/langchain/model_laboratory.py/0 | {
"file_path": "langchain/libs/langchain/langchain/model_laboratory.py",
"repo_id": "langchain",
"token_count": 1433
} | 532 |
<!--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 applicable law or agreed... | transformers/docs/source/ja/model_doc/deberta.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/deberta.md",
"repo_id": "transformers",
"token_count": 3598
} | 543 |
<!--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/en/model_doc/upernet.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/upernet.md",
"repo_id": "transformers",
"token_count": 1188
} | 467 |
python_tests()
| llama_index/llama-index-integrations/output_parsers/llama-index-output-parsers-guardrails/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/output_parsers/llama-index-output-parsers-guardrails/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,258 |
# Using Graph Stores
## `Neo4jGraphStore`
`Neo4j` is supported as a graph store integration. You can persist, visualize, and query graphs using LlamaIndex and Neo4j. Furthermore, existing Neo4j graphs are directly supported using `text2cypher` and the `KnowledgeGraphQueryEngine`.
If you've never used Neo4j before, y... | llama_index/docs/community/integrations/graph_stores.md/0 | {
"file_path": "llama_index/docs/community/integrations/graph_stores.md",
"repo_id": "llama_index",
"token_count": 612
} | 1,085 |
version: '3.5'
services:
etcd:
image: quay.io/coreos/etcd:v3.5.5
environment:
- ETCD_AUTO_COMPACTION_MODE=revision
- ETCD_AUTO_COMPACTION_RETENTION=1000
- ETCD_QUOTA_BACKEND_BYTES=4294967296
- ETCD_SNAPSHOT_COUNT=50000
volumes:
- ${DOCKER_VOLUME_DIRECTORY:-.}/volumes/etcd:/e... | milvus/deployments/docker/dev/docker-compose.yml/0 | {
"file_path": "milvus/deployments/docker/dev/docker-compose.yml",
"repo_id": "milvus",
"token_count": 1699
} | 1,848 |
import { IEmbeddingFunction } from "./IEmbeddingFunction";
interface CohereAIAPI {
createEmbedding: (params: {
model: string;
input: string[];
}) => Promise<number[][]>;
}
class CohereAISDK56 implements CohereAIAPI {
private cohereClient: any;
private apiKey: string;
constructor(configuration: { ap... | chroma/clients/js/src/embeddings/CohereEmbeddingFunction.ts/0 | {
"file_path": "chroma/clients/js/src/embeddings/CohereEmbeddingFunction.ts",
"repo_id": "chroma",
"token_count": 1214
} | 34 |
import { MyScaleStore } from "@langchain/community/vectorstores/myscale";
import { OpenAIEmbeddings } from "@langchain/openai";
const vectorStore = await MyScaleStore.fromTexts(
["Hello world", "Bye bye", "hello nice world"],
[
{ id: 2, name: "2" },
{ id: 1, name: "1" },
{ id: 3, name: "3" },
],
ne... | langchainjs/examples/src/indexes/vector_stores/myscale_fromTexts.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/myscale_fromTexts.ts",
"repo_id": "langchainjs",
"token_count": 324
} | 786 |
# Embeddings
##### FAQ
1. [How to use a custom/local embedding model?](#1-how-to-use-a-customlocal-embedding-model)
2. [How to use a local hugging face embedding model?](#2-how-to-use-a-local-hugging-face-embedding-model)
3. [How to use embedding model to generate embeddings for text?](#3-how-to-use-embedding-model-t... | llama_index/docs/community/faq/embeddings.md/0 | {
"file_path": "llama_index/docs/community/faq/embeddings.md",
"repo_id": "llama_index",
"token_count": 456
} | 1,087 |
# LlamaIndex Embeddings Integration: Azure Openai
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-azure-openai/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,267 |
<!--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/de/model_sharing.md/0 | {
"file_path": "transformers/docs/source/de/model_sharing.md",
"repo_id": "transformers",
"token_count": 4283
} | 447 |
# 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 applicabl... | transformers/src/transformers/models/clipseg/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/clipseg/__init__.py",
"repo_id": "transformers",
"token_count": 864
} | 613 |
python_sources()
| llama_index/llama-index-integrations/storage/chat_store/llama-index-storage-chat-store-redis/llama_index/storage/chat_store/redis/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/chat_store/llama-index-storage-chat-store-redis/llama_index/storage/chat_store/redis/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,401 |
import base64
import email
from enum import Enum
from typing import Any, Dict, List, Optional, Type
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_community.tools.gmail.base import GmailBaseTool
from langchain_community.tools.gmail... | langchain/libs/community/langchain_community/tools/gmail/search.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/gmail/search.py",
"repo_id": "langchain",
"token_count": 2262
} | 299 |
<!--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/en/model_doc/clipseg.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/clipseg.md",
"repo_id": "transformers",
"token_count": 1221
} | 471 |
<jupyter_start><jupyter_text>Optimized Embedding Model using Optimum-IntelLlamaIndex has support for loading quantized embedding models for Intel, using the [Optimum-Intel library](https://huggingface.co/docs/optimum/main/en/intel/index). Optimized models are smaller and faster, with minimal accuracy loss, see the [doc... | llama_index/docs/examples/embeddings/optimum_intel.ipynb/0 | {
"file_path": "llama_index/docs/examples/embeddings/optimum_intel.ipynb",
"repo_id": "llama_index",
"token_count": 419
} | 1,059 |
import { ChatOpenAI } from "@langchain/openai";
const chatModel = new ChatOpenAI({
modelName: "gpt-4",
callbacks: [
{
handleLLMEnd(output) {
console.log(JSON.stringify(output, null, 2));
},
},
],
});
await chatModel.invoke("Tell me a joke.");
/*
{
"generations": [
[
... | langchainjs/examples/src/models/chat/token_usage_tracking.ts/0 | {
"file_path": "langchainjs/examples/src/models/chat/token_usage_tracking.ts",
"repo_id": "langchainjs",
"token_count": 562
} | 827 |
import importlib
import json
import os
from typing import Any, Dict, List, Optional
from langchain_core._api import beta
from langchain_core.load.mapping import (
_OG_SERIALIZABLE_MAPPING,
OLD_CORE_NAMESPACES_MAPPING,
SERIALIZABLE_MAPPING,
)
from langchain_core.load.serializable import Serializable
DEFAUL... | langchain/libs/core/langchain_core/load/load.py/0 | {
"file_path": "langchain/libs/core/langchain_core/load/load.py",
"repo_id": "langchain",
"token_count": 2530
} | 413 |
// A scheduler recieves embedding records for a given batch of documents
// and schedules them to be ingested to the segment manager
use crate::{
system::{Component, ComponentContext, Handler, Receiver},
types::EmbeddingRecord,
};
use async_trait::async_trait;
use rand::prelude::SliceRandom;
use rand::Rng;
use... | chroma/rust/worker/src/ingest/scheduler.rs/0 | {
"file_path": "chroma/rust/worker/src/ingest/scheduler.rs",
"repo_id": "chroma",
"token_count": 4057
} | 56 |
<jupyter_start><jupyter_text>Chroma>[Chroma](https://docs.trychroma.com/getting-started) is a AI-native open-source vector database focused on developer productivity and happiness. Chroma is licensed under Apache 2.0.Install Chroma with:```shpip install chromadb```Chroma runs in various modes. See below for examples of... | langchain/docs/docs/integrations/vectorstores/chroma.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/chroma.ipynb",
"repo_id": "langchain",
"token_count": 3454
} | 180 |
from langchain_community.vectorstores.tair import Tair
__all__ = ["Tair"]
| langchain/libs/langchain/langchain/vectorstores/tair.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/tair.py",
"repo_id": "langchain",
"token_count": 25
} | 609 |
# Copyright 2024 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... | diffusers/src/diffusers/models/t5_film_transformer.py/0 | {
"file_path": "diffusers/src/diffusers/models/t5_film_transformer.py",
"repo_id": "diffusers",
"token_count": 1343
} | 229 |
import "@tensorflow/tfjs-backend-cpu";
import { TensorFlowEmbeddings } from "@langchain/community/embeddings/tensorflow";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { Document } from "@langchain/core/documents";
const embeddings = new TensorFlowEmbeddings();
const store = new MemoryVecto... | langchainjs/examples/src/models/embeddings/tensorflow.ts/0 | {
"file_path": "langchainjs/examples/src/models/embeddings/tensorflow.ts",
"repo_id": "langchainjs",
"token_count": 163
} | 901 |
from __future__ import annotations
from llama_index.core.storage.index_store.keyval_index_store import KVIndexStore
from llama_index.storage.kvstore.dynamodb import DynamoDBKVStore
class DynamoDBIndexStore(KVIndexStore):
def __init__(self, dynamodb_kvstore: DynamoDBKVStore, namespace: str | None = None):
... | llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-dynamodb/llama_index/storage/index_store/dynamodb/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/storage/index_store/llama-index-storage-index-store-dynamodb/llama_index/storage/index_store/dynamodb/base.py",
"repo_id": "llama_index",
"token_count": 303
} | 1,552 |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The 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/LICEN... | transformers/src/transformers/optimization.py/0 | {
"file_path": "transformers/src/transformers/optimization.py",
"repo_id": "transformers",
"token_count": 13951
} | 705 |
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