text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
from __future__ import annotations
from typing import TYPE_CHECKING, List, Optional
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
from langchain_community.utilities.vertexai import get_client_info
if TYPE_CHECKING:
from google.auth.credentials imp... | langchain/libs/community/langchain_community/document_loaders/bigquery.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/bigquery.py",
"repo_id": "langchain",
"token_count": 1512
} | 232 |
import { ChatFireworks } from "@langchain/community/chat_models/fireworks";
const model = new ChatFireworks({
temperature: 0.9,
// In Node.js defaults to process.env.FIREWORKS_API_KEY
fireworksApiKey: "YOUR-API-KEY",
});
| langchainjs/examples/src/models/chat/integration_fireworks.ts/0 | {
"file_path": "langchainjs/examples/src/models/chat/integration_fireworks.ts",
"repo_id": "langchainjs",
"token_count": 77
} | 803 |
import { test } from "@jest/globals";
import { ChatOpenAI } from "@langchain/openai";
import { Client, Example, Run } from "langsmith";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { BaseChatModel } from "@langchain/core/language_models/chat_models";
import { LLM } from "@langch... | langchainjs/langchain/src/smith/tests/runner_utils.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/smith/tests/runner_utils.int.test.ts",
"repo_id": "langchainjs",
"token_count": 3405
} | 936 |
"""Init params."""
from llama_index.legacy.core.response.schema import Response
__all__ = ["Response"]
| llama_index/llama-index-legacy/llama_index/legacy/response/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/response/__init__.py",
"repo_id": "llama_index",
"token_count": 34
} | 1,597 |
# Amazon Product Extraction Pack
This LlamaPack provides an example of our Amazon product extraction pack.
It loads in a website URL, screenshots the page. Then we use OpenAI GPT-4V + prompt engineering to extract the screenshot into a structured JSON output.
Check out the [notebook here](https://github.com/run-llam... | llama_index/llama-index-packs/llama-index-packs-amazon-product-extraction/README.md/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-amazon-product-extraction/README.md",
"repo_id": "llama_index",
"token_count": 542
} | 1,641 |
#!/usr/bin/env python
# coding=utf-8
# Copyright The HuggingFace Team 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.ap... | transformers/examples/pytorch/multiple-choice/run_swag_no_trainer.py/0 | {
"file_path": "transformers/examples/pytorch/multiple-choice/run_swag_no_trainer.py",
"repo_id": "transformers",
"token_count": 11876
} | 550 |
import CodeBlock from "@theme/CodeBlock";
# 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.
<a href="https://discord.gg/MMeYNTmh3x" target="_blank">
<img src="https://img.s... | langchainjs/docs/core_docs/docs/integrations/vectorstores/chroma.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/vectorstores/chroma.mdx",
"repo_id": "langchainjs",
"token_count": 838
} | 717 |
# coding=utf-8
# Copyright The HuggingFace Team 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/LICE... | transformers/src/transformers/models/rembert/tokenization_rembert.py/0 | {
"file_path": "transformers/src/transformers/models/rembert/tokenization_rembert.py",
"repo_id": "transformers",
"token_count": 4632
} | 652 |
import type { BaseLanguageModelInterface } from "@langchain/core/language_models/base";
import type {
StructuredToolInterface,
ToolInterface,
} from "@langchain/core/tools";
import { CallbackManager } from "@langchain/core/callbacks/manager";
import { BufferMemory } from "../memory/buffer_memory.js";
import { ChatA... | langchainjs/langchain/src/agents/initialize.ts/0 | {
"file_path": "langchainjs/langchain/src/agents/initialize.ts",
"repo_id": "langchainjs",
"token_count": 3108
} | 839 |
from pathlib import Path
from langchain.llms import OpenAI
import pickle
from langchain.chains import RetrievalQA
DIR_PATH = Path(__file__).parent
def get_chain():
with open(DIR_PATH / "vectorstore.pkl", "rb") as f:
vectorstore = pickle.load(f)
return RetrievalQA.from_chain_type(
llm=OpenAI(t... | langchain-aiplugin/retrieval_qa/chain.py/0 | {
"file_path": "langchain-aiplugin/retrieval_qa/chain.py",
"repo_id": "langchain-aiplugin",
"token_count": 169
} | 61 |
"""Init params."""
| llama_index/llama-index-legacy/llama_index/legacy/finetuning/openai/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/finetuning/openai/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,709 |
"""Json agent."""
| langchain/libs/langchain/langchain/agents/agent_toolkits/json/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/agents/agent_toolkits/json/__init__.py",
"repo_id": "langchain",
"token_count": 7
} | 479 |
<jupyter_start><jupyter_text>Chat Engine - Context Mode ContextChatEngine is a simple chat mode built on top of a retriever over your data. For each chat interaction:* first retrieve text from the index using the user message* set the retrieved text as context in the system prompt* return an answer to the user message ... | llama_index/docs/examples/chat_engine/chat_engine_context.ipynb/0 | {
"file_path": "llama_index/docs/examples/chat_engine/chat_engine_context.ipynb",
"repo_id": "llama_index",
"token_count": 1378
} | 1,091 |
{% set redirect = pathto(redirects[pagename]) %}
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="Refresh" content="0; url={{ redirect }}" />
<meta name="robots" content="follow, index">
<meta name="Descri... | langchain/docs/api_reference/templates/redirects.html/0 | {
"file_path": "langchain/docs/api_reference/templates/redirects.html",
"repo_id": "langchain",
"token_count": 226
} | 80 |
"""Init params."""
from llama_index.readers.huggingface_fs.base import HuggingFaceFSReader
__all__ = ["HuggingFaceFSReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-huggingface-fs/llama_index/readers/huggingface_fs/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-huggingface-fs/llama_index/readers/huggingface_fs/__init__.py",
"repo_id": "llama_index",
"token_count": 43
} | 1,414 |
# 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 required by appl... | transformers/src/transformers/models/fuyu/convert_fuyu_model_weights_to_hf.py/0 | {
"file_path": "transformers/src/transformers/models/fuyu/convert_fuyu_model_weights_to_hf.py",
"repo_id": "transformers",
"token_count": 1851
} | 610 |
[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 = ["SimpleArangoDBReader"]
contains_example = false
import_path = "llama_index.readers.arango... | llama_index/llama-index-integrations/readers/llama-index-readers-arango-db/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-arango-db/pyproject.toml",
"repo_id": "llama_index",
"token_count": 663
} | 1,463 |
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.packs.resume_screener import ResumeScreenerPack
def test_class():
names_of_base_classes = [b.__name__ for b in ResumeScreenerPack.__mro__]
assert BaseLlamaPack.__name__ in names_of_base_classes
| llama_index/llama-index-packs/llama-index-packs-resume-screener/tests/test_packs_resume_screener.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-resume-screener/tests/test_packs_resume_screener.py",
"repo_id": "llama_index",
"token_count": 103
} | 1,697 |
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import { CohereEmbeddings } from "@langchain/community/embeddings/cohere";
import { MultiQueryRetriever } from "langchain/retrievers/multi_query";
import { LLMChain } from "langchain/chains";
import { pull } from "langchain/hub";
import { BaseOutputPars... | langchainjs/examples/src/retrievers/multi_query_custom.ts/0 | {
"file_path": "langchainjs/examples/src/retrievers/multi_query_custom.ts",
"repo_id": "langchainjs",
"token_count": 1138
} | 848 |
# coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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.a... | transformers/src/transformers/benchmark/benchmark.py/0 | {
"file_path": "transformers/src/transformers/benchmark/benchmark.py",
"repo_id": "transformers",
"token_count": 4892
} | 589 |
"""Test AI21LLM llm."""
from langchain_ai21.llms import AI21LLM
def _generate_llm() -> AI21LLM:
"""
Testing AI21LLm using non default parameters with the following parameters
"""
return AI21LLM(
model="j2-ultra",
max_tokens=2, # Use less tokens for a faster response
temperat... | langchain/libs/partners/ai21/tests/integration_tests/test_llms.py/0 | {
"file_path": "langchain/libs/partners/ai21/tests/integration_tests/test_llms.py",
"repo_id": "langchain",
"token_count": 1071
} | 617 |
from langchain_community.vectorstores.vald import Vald
__all__ = ["Vald"]
| langchain/libs/langchain/langchain/vectorstores/vald.py/0 | {
"file_path": "langchain/libs/langchain/langchain/vectorstores/vald.py",
"repo_id": "langchain",
"token_count": 24
} | 610 |
# PNASNet
**Progressive Neural Architecture Search**, or **PNAS**, is a method for learning the structure of convolutional neural networks (CNNs). It uses a sequential model-based optimization (SMBO) strategy, where we search the space of cell structures, starting with simple (shallow) models and progressing to comple... | pytorch-image-models/docs/models/.templates/models/pnasnet.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/pnasnet.md",
"repo_id": "pytorch-image-models",
"token_count": 813
} | 359 |
import uuid
from typing import Callable, Optional
import pytest
from langchain_core.embeddings import Embeddings
from langchain_community.vectorstores import Qdrant
from tests.integration_tests.vectorstores.fake_embeddings import (
ConsistentFakeEmbeddings,
)
@pytest.mark.parametrize(
["embeddings", "embedd... | langchain/libs/community/tests/integration_tests/vectorstores/qdrant/test_embedding_interface.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/vectorstores/qdrant/test_embedding_interface.py",
"repo_id": "langchain",
"token_count": 656
} | 352 |
<jupyter_start><jupyter_text>Wikipedia>[Wikipedia](https://wikipedia.org/) is a multilingual free online encyclopedia written and maintained by a community of volunteers, known as Wikipedians, through open collaboration and using a wiki-based editing system called MediaWiki. `Wikipedia` is the largest and most-read ref... | langchain/docs/docs/integrations/tools/wikipedia.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/wikipedia.ipynb",
"repo_id": "langchain",
"token_count": 172
} | 172 |
import { StreamEvent } from "../tracers/log_stream.js";
/**
* Utility to filter the root event in the streamEvents implementation.
* This is simply binding the arguments to the namespace to make save on
* a bit of typing in the streamEvents implementation.
*
* TODO: Refactor and remove.
*/
export class _RootEven... | langchainjs/langchain-core/src/runnables/utils.ts/0 | {
"file_path": "langchainjs/langchain-core/src/runnables/utils.ts",
"repo_id": "langchainjs",
"token_count": 667
} | 904 |
from .rl import ValueGuidedRLPipeline
| diffusers/src/diffusers/experimental/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/experimental/__init__.py",
"repo_id": "diffusers",
"token_count": 12
} | 220 |
# 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/speecht5/test_modeling_speecht5.py/0 | {
"file_path": "transformers/tests/models/speecht5/test_modeling_speecht5.py",
"repo_id": "transformers",
"token_count": 35083
} | 825 |
import { HumanMessage, SystemMessage } from "@langchain/core/messages";
import { AutoGPTPrompt } from "../prompt.js";
// Mock token counter function
const mockTokenCounter = async (text: string): Promise<number> => text.length;
// Mock vector store retriever interface
// Todo: replace any with actual interface
// esl... | langchainjs/langchain/src/experimental/autogpt/tests/prompt.test.ts/0 | {
"file_path": "langchainjs/langchain/src/experimental/autogpt/tests/prompt.test.ts",
"repo_id": "langchainjs",
"token_count": 1012
} | 919 |
# LlamaIndex Vector_Stores Integration: Faiss
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-faiss/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-faiss/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,606 |
from typing import Any, Dict, List, Optional, Sequence, Tuple
from llama_index.legacy.core.llms.types import ChatMessage, MessageRole
from llama_index.legacy.llms.generic_utils import get_from_param_or_env
DEFAULT_ANYSCALE_API_BASE = "https://api.endpoints.anyscale.com/v1"
DEFAULT_ANYSCALE_API_VERSION = ""
LLAMA_MOD... | llama_index/llama-index-legacy/llama_index/legacy/llms/anyscale_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/llms/anyscale_utils.py",
"repo_id": "llama_index",
"token_count": 1507
} | 1,677 |
import { Drawer } from "vaul";
import { ReactNode, useEffect, useMemo, useRef, useState } from "react";
import CodeIcon from "../assets/CodeIcon.svg?react";
import PadlockIcon from "../assets/PadlockIcon.svg?react";
import CopyIcon from "../assets/CopyIcon.svg?react";
import CheckCircleIcon from "../assets/CheckCircleI... | langserve/langserve/playground/src/components/ShareDialog.tsx/0 | {
"file_path": "langserve/langserve/playground/src/components/ShareDialog.tsx",
"repo_id": "langserve",
"token_count": 2444
} | 1,050 |
import type { MessageUpdate } from "./MessageUpdate";
import type { Timestamps } from "./Timestamps";
import type { WebSearch } from "./WebSearch";
export type Message = Partial<Timestamps> & {
from: "user" | "assistant" | "system";
id: ReturnType<typeof crypto.randomUUID>;
content: string;
updates?: MessageUpdate... | chat-ui/src/lib/types/Message.ts/0 | {
"file_path": "chat-ui/src/lib/types/Message.ts",
"repo_id": "chat-ui",
"token_count": 210
} | 102 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle::{DType, IndexOp, D};
use candle_nn::{Module, VarBuilder};
use candle_transformers::models::resnet;
use clap::{Parser, ValueEnum};
#[derive(Clone, Copy, Debug, ValueEnum)]
enum Which {
#[val... | candle/candle-examples/examples/resnet/main.rs/0 | {
"file_path": "candle/candle-examples/examples/resnet/main.rs",
"repo_id": "candle",
"token_count": 1281
} | 47 |
# candle-trocr
`TrOCR` is a transformer OCR Model. In this example it is used to
transcribe image text. See the associated [model
card](https://huggingface.co/microsoft/trocr-base-printed) for details on
the model itself.
Supported models include:
- `--which base`: small handwritten OCR model.
- `--which large`: lar... | candle/candle-examples/examples/trocr/readme.md/0 | {
"file_path": "candle/candle-examples/examples/trocr/readme.md",
"repo_id": "candle",
"token_count": 360
} | 49 |
from typing import Any, List, Optional
from llama_index.legacy.callbacks.base import CallbackManager
from llama_index.legacy.callbacks.schema import CBEventType, EventPayload
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
from llama_index.legacy.core.base_retriever import BaseRetriever
from llam... | llama_index/llama-index-legacy/llama_index/legacy/indices/managed/vectara/query.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/managed/vectara/query.py",
"repo_id": "llama_index",
"token_count": 2266
} | 1,566 |
<!--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 applicable law or agreed... | diffusers/docs/source/ko/optimization/mps.md/0 | {
"file_path": "diffusers/docs/source/ko/optimization/mps.md",
"repo_id": "diffusers",
"token_count": 2532
} | 178 |
import logging
import random
import gevent
# import gevent.monkey
# gevent.monkey.patch_all()
from locust import User, between, events, stats
from locust.env import Environment
import locust.stats
import math
from locust import LoadTestShape
from locust.stats import stats_printer, print_stats
# from locust.log import s... | milvus/tests/benchmark/milvus_benchmark/runners/locust_user.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/runners/locust_user.py",
"repo_id": "milvus",
"token_count": 1765
} | 1,993 |
use crate::models::with_tracing::{conv2d, linear, linear_no_bias, Conv2d, Linear};
use candle::{IndexOp, Module, Result, Tensor, D};
use candle_nn::{layer_norm, LayerNorm, VarBuilder};
// https://github.com/huggingface/transformers/blob/main/src/transformers/models/vit/configuration_vit.py
#[derive(Debug, Clone, serde... | candle/candle-transformers/src/models/vit.rs/0 | {
"file_path": "candle/candle-transformers/src/models/vit.rs",
"repo_id": "candle",
"token_count": 5870
} | 79 |
"""Google Finance API Toolkit."""
from langchain_community.tools.google_finance.tool import GoogleFinanceQueryRun
__all__ = ["GoogleFinanceQueryRun"]
| langchain/libs/langchain/langchain/tools/google_finance/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/google_finance/__init__.py",
"repo_id": "langchain",
"token_count": 44
} | 602 |
import fs from "fs";
import { GoogleVertexAIMultimodalEmbeddings } from "langchain/experimental/multimodal_embeddings/googlevertexai";
import { FaissStore } from "@langchain/community/vectorstores/faiss";
import { Document } from "@langchain/core/documents";
const embeddings = new GoogleVertexAIMultimodalEmbeddings();... | langchainjs/examples/src/models/embeddings/googlevertexai_multimodal_advanced.ts/0 | {
"file_path": "langchainjs/examples/src/models/embeddings/googlevertexai_multimodal_advanced.ts",
"repo_id": "langchainjs",
"token_count": 613
} | 851 |
# 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/amused/test_amused_img2img.py/0 | {
"file_path": "diffusers/tests/pipelines/amused/test_amused_img2img.py",
"repo_id": "diffusers",
"token_count": 3982
} | 286 |
---
sidebar_class_name: hidden
---
# Stores
Storing data in key value format is quick and efficient, and can be a powerful tool for LLM applications. The `BaseStore` class provides a simple interface for getting, setting, deleting and iterating over lists of key value pairs.
The public API of `BaseStore` in LangChai... | langchainjs/docs/core_docs/docs/integrations/stores/index.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/stores/index.mdx",
"repo_id": "langchainjs",
"token_count": 1706
} | 735 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-arango-db/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-arango-db/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,462 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.telegram import TelegramReader
def test_class():
names_of_base_classes = [b.__name__ for b in TelegramReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-telegram/tests/test_readers_telegram.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-telegram/tests/test_readers_telegram.py",
"repo_id": "llama_index",
"token_count": 86
} | 1,559 |
""" Bring-Your-Own-Attention Network
A flexible network w/ dataclass based config for stacking NN blocks including
self-attention (or similar) layers.
Currently used to implement experimental variants of:
* Bottleneck Transformers
* Lambda ResNets
* HaloNets
Consider all of the models definitions here as exper... | pytorch-image-models/timm/models/byoanet.py/0 | {
"file_path": "pytorch-image-models/timm/models/byoanet.py",
"repo_id": "pytorch-image-models",
"token_count": 9703
} | 340 |
<jupyter_start><jupyter_text>IntroductionThis notebook is going to cover the basics of how to use Stable Diffusion to create and modify images using existing pipelines. We'll also take a brief look at the key components within the pipeline, while leaving further exploration of them to the deep dive notebook. Specifical... | diffusion-models-class/units/en/unit3/stable_diffusion_introduction.ipynb/0 | {
"file_path": "diffusion-models-class/units/en/unit3/stable_diffusion_introduction.ipynb",
"repo_id": "diffusion-models-class",
"token_count": 6232
} | 306 |
import os
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_community.document_loaders import PyPDFLoader
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_community.vectorstores import MongoDBAtlasVectorSearch
from pymongo import MongoClient
MONGO_URI = os.env... | langchain/templates/rag-mongo/ingest.py/0 | {
"file_path": "langchain/templates/rag-mongo/ingest.py",
"repo_id": "langchain",
"token_count": 453
} | 664 |
# coding=utf-8
# Copyright 2021 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/wav2vec2/processing_wav2vec2.py/0 | {
"file_path": "transformers/src/transformers/models/wav2vec2/processing_wav2vec2.py",
"repo_id": "transformers",
"token_count": 2839
} | 674 |
<jupyter_start><jupyter_text>Interacting with Embeddings deployed in Amazon SageMaker Endpoint with LlamaIndexAn Amazon SageMaker endpoint is a fully managed resource that enables the deployment of machine learning models, for making predictions on new data.This notebook demonstrates how to interact with Embedding endp... | llama_index/docs/examples/embeddings/sagemaker_embedding_endpoint.ipynb/0 | {
"file_path": "llama_index/docs/examples/embeddings/sagemaker_embedding_endpoint.ipynb",
"repo_id": "llama_index",
"token_count": 985
} | 1,054 |
<jupyter_start><jupyter_code>import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
from peft import PeftConfig, PeftModel
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM, AutoTokenizer
from datasets import load_dataset
import torch
import random
peft_model_id = "smangrul/tinyllama_lo... | peft/examples/multi_adapter_examples/Lora_Merging.ipynb/0 | {
"file_path": "peft/examples/multi_adapter_examples/Lora_Merging.ipynb",
"repo_id": "peft",
"token_count": 1305
} | 330 |
accuracy:
collections:
-
milvus:
db_config.primary_path: /test/milvus/db_data_011/sift_10m_128_l2_sq8
cache_config.cpu_cache_capacity: 32GB
engine_config.use_blas_threshold: 1100
engine_config.gpu_search_threshold: 1
gpu_resource_config.enable: true
gpu_resour... | milvus/tests/benchmark/milvus_benchmark/suites/2_cpu_accuracy.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/2_cpu_accuracy.yaml",
"repo_id": "milvus",
"token_count": 333
} | 2,147 |
Verify user is able to easily customize Milvus deployment with various configuration items.
To be updated... | milvus/tests/python_client/customize/README.md/0 | {
"file_path": "milvus/tests/python_client/customize/README.md",
"repo_id": "milvus",
"token_count": 23
} | 1,967 |
# coding=utf-8
# Copyright 2023 The HuggingFace Team 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 ... | transformers/tests/bettertransformer/test_integration.py/0 | {
"file_path": "transformers/tests/bettertransformer/test_integration.py",
"repo_id": "transformers",
"token_count": 1117
} | 697 |
/*
* 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... | milvus/pkg/util/expr/expr.go/0 | {
"file_path": "milvus/pkg/util/expr/expr.go",
"repo_id": "milvus",
"token_count": 725
} | 1,826 |
<jupyter_start><jupyter_text>Building Evaluation from ScratchWe show how you can build evaluation modules from scratch. This includes both evaluation of the final generated response (where the output is plain text), as well as the evaluation of retrievers (where the output is a ranked list of items).We have in-house mo... | llama_index/docs/examples/low_level/evaluation.ipynb/0 | {
"file_path": "llama_index/docs/examples/low_level/evaluation.ipynb",
"repo_id": "llama_index",
"token_count": 5132
} | 1,147 |
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.packs.rag_cli_local import LocalRAGCLIPack
def test_class():
names_of_base_classes = [b.__name__ for b in LocalRAGCLIPack.__mro__]
assert BaseLlamaPack.__name__ in names_of_base_classes
| llama_index/llama-index-packs/llama-index-packs-rag-cli-local/tests/test_packs_rag_cli_local.py/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-rag-cli-local/tests/test_packs_rag_cli_local.py",
"repo_id": "llama_index",
"token_count": 100
} | 1,718 |
<jupyter_start><jupyter_text>**Fine-tuning for Image Classification with 🤗 Transformers**This notebook shows how to fine-tune any pretrained Vision model for Image Classification on a custom dataset. The idea is to add a randomly initialized classification head on top of a pre-trained encoder, and fine-tune the model ... | notebooks/examples/image_classification_albumentations.ipynb/0 | {
"file_path": "notebooks/examples/image_classification_albumentations.ipynb",
"repo_id": "notebooks",
"token_count": 7695
} | 300 |
<!---
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 ... | transformers/examples/pytorch/semantic-segmentation/README.md/0 | {
"file_path": "transformers/examples/pytorch/semantic-segmentation/README.md",
"repo_id": "transformers",
"token_count": 3408
} | 589 |
# LlamaIndex Program Integration: Lmformatenforcer
| llama_index/llama-index-integrations/program/llama-index-program-lmformatenforcer/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/program/llama-index-program-lmformatenforcer/README.md",
"repo_id": "llama_index",
"token_count": 13
} | 1,330 |
poetry_requirements(
name="poetry",
)
python_requirements(
name="reqs",
)
| llama_index/llama-index-packs/llama-index-packs-streamlit-chatbot/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-streamlit-chatbot/BUILD",
"repo_id": "llama_index",
"token_count": 36
} | 1,608 |
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Iterable, List, Optional
if TYPE_CHECKING:
from pyspark.sql import DataFrame, Row, SparkSession
class SparkSQL:
"""SparkSQL is a utility class for interacting with Spark SQL."""
def __init__(
self,
spark_session: ... | langchain/libs/community/langchain_community/utilities/spark_sql.py/0 | {
"file_path": "langchain/libs/community/langchain_community/utilities/spark_sql.py",
"repo_id": "langchain",
"token_count": 3289
} | 309 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package writebuffer
import (
context "context"
msgpb "github.com/milvus-io/milvus-proto/go-api/v2/msgpb"
mock "github.com/stretchr/testify/mock"
msgstream "github.com/milvus-io/milvus/pkg/mq/msgstream"
)
// MockWriteBuffer is an autogenerated mock type for the... | milvus/internal/datanode/writebuffer/mock_write_buffer.go/0 | {
"file_path": "milvus/internal/datanode/writebuffer/mock_write_buffer.go",
"repo_id": "milvus",
"token_count": 4698
} | 1,982 |
// 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/src/segcore/ConcurrentVector.cpp/0 | {
"file_path": "milvus/internal/core/src/segcore/ConcurrentVector.cpp",
"repo_id": "milvus",
"token_count": 2245
} | 1,797 |
import os
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_community.chat_models import ChatOpenAI
from langchain_community.document_loaders import WebBaseLoader
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_community.vectorstores import Weaviate
from langc... | langchain/templates/rag-weaviate/rag_weaviate/chain.py/0 | {
"file_path": "langchain/templates/rag-weaviate/rag_weaviate/chain.py",
"repo_id": "langchain",
"token_count": 657
} | 751 |
# Model arguments
model_name_or_path: alignment-handbook/zephyr-7b-sft-full
# Data training arguments
# For definitions, see: src/h4/training/config.py
dataset_mixer:
HuggingFaceH4/ultrafeedback_binarized: 1.0
dataset_splits:
- train_prefs
- test_prefs
preprocessing_num_workers: 12
# DPOTrainer arguments
bf16: true... | alignment-handbook/tests/fixtures/config_dpo_full.yaml/0 | {
"file_path": "alignment-handbook/tests/fixtures/config_dpo_full.yaml",
"repo_id": "alignment-handbook",
"token_count": 329
} | 30 |
import type { ObjectId } from "mongodb";
import type { Timestamps } from "./Timestamps";
export interface User extends Timestamps {
_id: ObjectId;
username?: string;
name: string;
email?: string;
avatarUrl: string;
hfUserId: string;
}
| chat-ui/src/lib/types/User.ts/0 | {
"file_path": "chat-ui/src/lib/types/User.ts",
"repo_id": "chat-ui",
"token_count": 83
} | 96 |
# Metric Card for Code Eval
## Metric description
The CodeEval metric estimates the pass@k metric for code synthesis.
It implements the evaluation harness for the HumanEval problem solving dataset described in the paper ["Evaluating Large Language Models Trained on Code"](https://arxiv.org/abs/2107.03374).
## How... | datasets/metrics/code_eval/README.md/0 | {
"file_path": "datasets/metrics/code_eval/README.md",
"repo_id": "datasets",
"token_count": 1698
} | 123 |
from typing import Any, List
from langchain_core.prompt_values import ImagePromptValue, ImageURL, PromptValue
from langchain_core.prompts.base import BasePromptTemplate
from langchain_core.pydantic_v1 import Field
from langchain_core.utils import image as image_utils
class ImagePromptTemplate(BasePromptTemplate[Imag... | langchain/libs/core/langchain_core/prompts/image.py/0 | {
"file_path": "langchain/libs/core/langchain_core/prompts/image.py",
"repo_id": "langchain",
"token_count": 1221
} | 417 |
from typing import Any, Dict, List, Union
from langchain_core.messages import BaseMessage, get_buffer_string
from langchain.memory.chat_memory import BaseChatMemory
class ConversationBufferWindowMemory(BaseChatMemory):
"""Buffer for storing conversation memory inside a limited size window."""
human_prefix:... | langchain/libs/langchain/langchain/memory/buffer_window.py/0 | {
"file_path": "langchain/libs/langchain/langchain/memory/buffer_window.py",
"repo_id": "langchain",
"token_count": 614
} | 554 |
"""Kùzu graph store index."""
from typing import Any, Dict, List, Optional
from llama_index.legacy.graph_stores.types import GraphStore
class KuzuGraphStore(GraphStore):
def __init__(
self,
database: Any,
node_table_name: str = "entity",
rel_table_name: str = "links",
**k... | llama_index/llama-index-legacy/llama_index/legacy/graph_stores/kuzu.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/graph_stores/kuzu.py",
"repo_id": "llama_index",
"token_count": 4551
} | 1,567 |
python_tests()
| llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-dynamodb/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-dynamodb/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,604 |
from text_generation.errors import (
parse_error,
GenerationError,
IncompleteGenerationError,
OverloadedError,
ValidationError,
BadRequestError,
ShardNotReadyError,
ShardTimeoutError,
NotFoundError,
RateLimitExceededError,
UnknownError,
)
def test_generation_error():
pa... | text-generation-inference/clients/python/tests/test_errors.py/0 | {
"file_path": "text-generation-inference/clients/python/tests/test_errors.py",
"repo_id": "text-generation-inference",
"token_count": 598
} | 394 |
import json
import logging
import sys
from typing import Any, List, Optional
from urllib.parse import urlparse
from llama_index.core.bridge.pydantic import Field
from llama_index.core.llms import ChatMessage
from llama_index.core.storage.chat_store.base import BaseChatStore
import redis
from redis import Redis
from r... | llama_index/llama-index-integrations/storage/chat_store/llama-index-storage-chat-store-redis/llama_index/storage/chat_store/redis/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/storage/chat_store/llama-index-storage-chat-store-redis/llama_index/storage/chat_store/redis/base.py",
"repo_id": "llama_index",
"token_count": 4051
} | 1,550 |
from typing import Any, Dict, List
class HugeGraph:
"""HugeGraph wrapper for graph operations.
*Security note*: Make sure that the database connection uses credentials
that are narrowly-scoped to only include necessary permissions.
Failure to do so may result in data corruption or loss, since... | langchain/libs/community/langchain_community/graphs/hugegraph.py/0 | {
"file_path": "langchain/libs/community/langchain_community/graphs/hugegraph.py",
"repo_id": "langchain",
"token_count": 1026
} | 257 |
{
"openapi": "3.0.1",
"info": {
"title": "Calculator Plugin",
"description": "A plugin that allows the user to perform basic arithmetic operations like addition, subtraction, multiplication, division, power, and square root using ChatGPT.",
"version": "v1"
},
"servers": [
{
... | langchain/libs/langchain/tests/unit_tests/examples/test_specs/calculator/apispec.json/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/examples/test_specs/calculator/apispec.json",
"repo_id": "langchain",
"token_count": 2147
} | 639 |
<!--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 applicable law or agreed... | diffusers/docs/source/zh/installation.md/0 | {
"file_path": "diffusers/docs/source/zh/installation.md",
"repo_id": "diffusers",
"token_count": 2455
} | 205 |
python_tests()
| llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-tensorrt/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-tensorrt/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,306 |
# coding=utf-8
# Copyright 2022 The OpenAI 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://www.apache.org/licenses/L... | transformers/src/transformers/models/whisper/modeling_tf_whisper.py/0 | {
"file_path": "transformers/src/transformers/models/whisper/modeling_tf_whisper.py",
"repo_id": "transformers",
"token_count": 37408
} | 741 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package task
import mock "github.com/stretchr/testify/mock"
// MockScheduler is an autogenerated mock type for the Scheduler type
type MockScheduler struct {
mock.Mock
}
type MockScheduler_Expecter struct {
mock *mock.Mock
}
func (_m *MockScheduler) EXPECT() *Mo... | milvus/internal/querycoordv2/task/mock_scheduler.go/0 | {
"file_path": "milvus/internal/querycoordv2/task/mock_scheduler.go",
"repo_id": "milvus",
"token_count": 4828
} | 1,760 |
# 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/wuerstchen/test_wuerstchen_prior.py/0 | {
"file_path": "diffusers/tests/pipelines/wuerstchen/test_wuerstchen_prior.py",
"repo_id": "diffusers",
"token_count": 4396
} | 260 |
"""
**Utility functions** for LangChain.
These functions do not depend on any other LangChain module.
"""
from langchain_core.utils.formatting import StrictFormatter, formatter
from langchain_core.utils.input import (
get_bolded_text,
get_color_mapping,
get_colored_text,
print_text,
)
from langchain_c... | langchain/libs/langchain/langchain/utils/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utils/__init__.py",
"repo_id": "langchain",
"token_count": 499
} | 567 |
# LlamaIndex Readers Integration: Chatgpt Plugin
| llama_index/llama-index-integrations/readers/llama-index-readers-chatgpt-plugin/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-chatgpt-plugin/README.md",
"repo_id": "llama_index",
"token_count": 12
} | 1,346 |
import { OpenAI } from "@langchain/openai";
import { loadSummarizationChain } from "langchain/chains";
import { RecursiveCharacterTextSplitter } from "langchain/text_splitter";
import * as fs from "fs";
// In this example, we use a `MapReduceDocumentsChain` specifically prompted to summarize a set of documents.
const ... | langchainjs/examples/src/chains/summarization_map_reduce_intermediate_steps.ts/0 | {
"file_path": "langchainjs/examples/src/chains/summarization_map_reduce_intermediate_steps.ts",
"repo_id": "langchainjs",
"token_count": 648
} | 792 |
locust_insert_performance:
collections:
-
milvus:
db_config.primary_path: /test/milvus/db_data_011/insert_sift_1m_128_l2_2
collection_name: local_1m_128_l2
ni_per: 50000
build_index: false
index_type: ivf_sq8
index_param:
nlist: 1024
task:
load_s... | milvus/tests/benchmark/milvus_benchmark/suites/2_locust_load_insert_flush.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/2_locust_load_insert_flush.yaml",
"repo_id": "milvus",
"token_count": 336
} | 1,869 |
from pymilvus.client.types import CompactionPlans
from pymilvus import Role
from utils.util_log import test_log as log
from common import common_type as ct
from common import common_func as cf
from common.common_type import CheckTasks, Connect_Object_Name
# from common.code_mapping import ErrorCode, ErrorMessage
from ... | milvus/tests/python_client/check/func_check.py/0 | {
"file_path": "milvus/tests/python_client/check/func_check.py",
"repo_id": "milvus",
"token_count": 12177
} | 2,118 |
use crate::{op::BackpropOp, op::Op, Error, Result, Tensor};
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct ParamsConv1D {
pub(crate) b_size: usize,
// Maybe we should have a version without l_in as this bit depends on the input and not only on
// the weights.
pub(crate) l_in: usize,
pub(crate) c... | candle/candle-core/src/conv.rs/0 | {
"file_path": "candle/candle-core/src/conv.rs",
"repo_id": "candle",
"token_count": 5388
} | 29 |
from langchain_community.utilities.requests import (
Requests,
RequestsWrapper,
TextRequestsWrapper,
)
__all__ = ["Requests", "TextRequestsWrapper", "RequestsWrapper"]
| langchain/libs/langchain/langchain/utilities/requests.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utilities/requests.py",
"repo_id": "langchain",
"token_count": 65
} | 565 |
"""**Tools** are classes that an Agent uses to interact with the world.
Each tool has a **description**. Agent uses the description to choose the right
tool for the job.
**Class hierarchy:**
.. code-block::
ToolMetaclass --> BaseTool --> <name>Tool # Examples: AIPluginTool, BaseGraphQLTool
... | langchain/libs/langchain/langchain/tools/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/__init__.py",
"repo_id": "langchain",
"token_count": 2290
} | 571 |
from langchain_core.load import __all__
EXPECTED_ALL = ["dumpd", "dumps", "load", "loads", "Serializable"]
def test_all_imports() -> None:
assert set(__all__) == set(EXPECTED_ALL)
| langchain/libs/core/tests/unit_tests/load/test_imports.py/0 | {
"file_path": "langchain/libs/core/tests/unit_tests/load/test_imports.py",
"repo_id": "langchain",
"token_count": 71
} | 405 |
# Airbyte Gong Loader
The Airbyte Gong Loader allows you to access different Gong objects.
## Installation
- Install llama_hub: `pip install llama_hub`
- Install the gong source: `pip install airbyte-source-gong`
## Usage
Here's an example usage of the AirbyteGongReader.
```python
from llama_hub.airbyte_gong impo... | llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-gong/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-gong/README.md",
"repo_id": "llama_index",
"token_count": 839
} | 1,332 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-promptlayer/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-promptlayer/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,213 |
LICENSE=$1
FOLDER=$2
if [ -z ${FOLDER} ] || [ -z ${LICENSE} ]; then
echo "usage $0 <path/to/license> <path/to/code_folder>"
exit
fi
cat ${LICENSE} > /dev/null || exit -1
FILES=`find ${FOLDER} \
| grep -E "(*\.cpp$|*\.h$|*\.cu$)" \
| grep -v thirdparty \
| grep -v cmake_build \
| grep -v cmake-build \
| grep ... | milvus/internal/core/build-support/add_cpp_license.sh/0 | {
"file_path": "milvus/internal/core/build-support/add_cpp_license.sh",
"repo_id": "milvus",
"token_count": 325
} | 1,914 |
[tool.poetry]
name = "text-generation-integration-tests"
version = "1.4.0"
description = "Text Generation Inference integration tests"
authors = ["Nicolas Patry <nicolas@huggingface.co>"]
[tool.poetry.dependencies]
python = ">=3.9,<3.13"
syrupy = "4.0.1"
text-generation = "^0.6.0"
pytest = "^7.4.0"
pytest-asyncio = "^... | text-generation-inference/integration-tests/pyproject.toml/0 | {
"file_path": "text-generation-inference/integration-tests/pyproject.toml",
"repo_id": "text-generation-inference",
"token_count": 151
} | 371 |
<p align="center">
<img src="https://raw.githubusercontent.com/huggingface/alignment-handbook/main/assets/handbook.png">
</p>
<p align="center">
🤗 <a href="https://huggingface.co/collections/alignment-handbook/handbook-v01-models-and-datasets-654e424d22e6880da5ebc015" target="_blank">Models & Datasets</a> | 📃 ... | alignment-handbook/README.md/0 | {
"file_path": "alignment-handbook/README.md",
"repo_id": "alignment-handbook",
"token_count": 2053
} | 23 |
# candle-kernels
This crate contains CUDA kernels used from candle. Some of these implementations
come from the [dfdx crate](https://github.com/coreylowman/dfdx).
| candle/candle-kernels/README.md/0 | {
"file_path": "candle/candle-kernels/README.md",
"repo_id": "candle",
"token_count": 45
} | 62 |
[tool.poetry]
name = "langchain-monorepo"
version = "0.0.1"
description = "LangChain mono-repo"
authors = []
license = "MIT"
readme = "README.md"
repository = "https://www.github.com/langchain-ai/langchain"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
[tool.poetry.group.docs.dependencies]
langchain = { path = ... | langchain/pyproject.toml/0 | {
"file_path": "langchain/pyproject.toml",
"repo_id": "langchain",
"token_count": 1157
} | 665 |
import { FewShotPromptTemplate, PromptTemplate } from "@langchain/core/prompts";
export const run = async () => {
// First, create a list of few-shot examples.
const examples = [
{ word: "happy", antonym: "sad" },
{ word: "tall", antonym: "short" },
];
// Next, we specify the template to format the ex... | langchainjs/examples/src/prompts/few_shot.ts/0 | {
"file_path": "langchainjs/examples/src/prompts/few_shot.ts",
"repo_id": "langchainjs",
"token_count": 552
} | 907 |
python_sources()
| llama_index/llama-index-integrations/evaluation/llama-index-evaluation-tonic-validate/llama_index/evaluation/tonic_validate/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/evaluation/llama-index-evaluation-tonic-validate/llama_index/evaluation/tonic_validate/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,206 |
# Copyright 2021 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... | accelerate/src/accelerate/test_utils/training.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/training.py",
"repo_id": "accelerate",
"token_count": 1572
} | 15 |
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