text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
import type {
launch,
WaitForOptions,
Page,
Browser,
PuppeteerLaunchOptions,
} from "puppeteer";
import { Document } from "@langchain/core/documents";
import { BaseDocumentLoader } from "../base.js";
import type { DocumentLoader } from "../base.js";
export { Page, Browser };
export type PuppeteerGotoOption... | langchainjs/langchain/src/document_loaders/web/puppeteer.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/web/puppeteer.ts",
"repo_id": "langchainjs",
"token_count": 1642
} | 872 |
// JS backend not used by default, see README for instructions.
import { NextRequest, NextResponse } from "next/server";
import { Client } from "langsmith";
export const runtime = "edge";
const client = new Client();
export async function POST(req: NextRequest) {
try {
const body = await req.json();
cons... | weblangchain/nextjs/app/api/feedback/route.ts/0 | {
"file_path": "weblangchain/nextjs/app/api/feedback/route.ts",
"repo_id": "weblangchain",
"token_count": 510
} | 2,149 |
import logging
from typing import Any, Dict, List, Mapping, Optional
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from langchain_core.pydantic_v1 import (
BaseModel,
Extra,
Field,
SecretStr,
root_validator,
)
from langchain_core.u... | langchain/libs/community/langchain_community/llms/pipelineai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/pipelineai.py",
"repo_id": "langchain",
"token_count": 1769
} | 291 |
<jupyter_start><jupyter_text>Fine Tuning GPT-3.5-TurboIn this notebook, we walk through an example of fine-tuning gpt-3.5-turbo.Specifically, we attempt to distill GPT-4's knowledge, by generating training data with GPT-4 to then fine-tune GPT-3.5.All training data is generated using two different sections of our index... | llama_index/experimental/openai_fine_tuning/openai_fine_tuning.ipynb/0 | {
"file_path": "llama_index/experimental/openai_fine_tuning/openai_fine_tuning.ipynb",
"repo_id": "llama_index",
"token_count": 3486
} | 1,170 |
// 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/rootcoord/garbage_collector.go/0 | {
"file_path": "milvus/internal/rootcoord/garbage_collector.go",
"repo_id": "milvus",
"token_count": 3277
} | 1,919 |
"""Weaviate-specific serializers for LlamaIndex data structures.
Contain conversion to and from dataclasses that LlamaIndex uses.
"""
import logging
from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
if TYPE_CHECKING:
from weaviate import Client
from llama_index.legacy.schema import BaseNode, Me... | llama_index/llama-index-legacy/llama_index/legacy/vector_stores/weaviate_utils.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/vector_stores/weaviate_utils.py",
"repo_id": "llama_index",
"token_count": 1931
} | 1,789 |
from typing import Any
from langchain_community.document_loaders.dataframe import BaseDataFrameLoader
class XorbitsLoader(BaseDataFrameLoader):
"""Load `Xorbits` DataFrame."""
def __init__(self, data_frame: Any, page_content_column: str = "text"):
"""Initialize with dataframe object.
Requir... | langchain/libs/community/langchain_community/document_loaders/xorbits.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/xorbits.py",
"repo_id": "langchain",
"token_count": 489
} | 263 |
import os
from langchain_community.retrievers.you import YouRetriever
class TestYouRetriever:
@classmethod
def setup_class(cls) -> None:
if not os.getenv("YDC_API_KEY"):
raise ValueError("YDC_API_KEY environment variable is not set")
def test_get_relevant_documents(self) -> None:
... | langchain/libs/community/tests/integration_tests/retrievers/test_you.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/retrievers/test_you.py",
"repo_id": "langchain",
"token_count": 175
} | 348 |
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { type BaseMessage } from "@langchain/core/messages";
import { type BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import {
BaseChatMod... | langchainjs/libs/langchain-google-common/src/chat_models.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-common/src/chat_models.ts",
"repo_id": "langchainjs",
"token_count": 1825
} | 1,059 |
python_sources()
| llama_index/llama-index-packs/llama-index-packs-timescale-vector-autoretrieval/llama_index/packs/timescale_vector_autoretrieval/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-timescale-vector-autoretrieval/llama_index/packs/timescale_vector_autoretrieval/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,737 |
import { GenerationChunk } from "@langchain/core/outputs";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { LLM, BaseLLMParams } from "@langchain/core/language_models/llms";
/**
* Interface for the input parameters specific to the Fake List model.
*/
export interface FakeListInp... | langchainjs/langchain/src/llms/fake.ts/0 | {
"file_path": "langchainjs/langchain/src/llms/fake.ts",
"repo_id": "langchainjs",
"token_count": 752
} | 928 |
"""LLM Chain for turning a user text query into a structured query."""
from __future__ import annotations
import json
from typing import Any, Callable, List, Optional, Sequence, Tuple, Union, cast
from langchain_core.exceptions import OutputParserException
from langchain_core.language_models import BaseLanguageModel
... | langchain/libs/langchain/langchain/chains/query_constructor/base.py/0 | {
"file_path": "langchain/libs/langchain/langchain/chains/query_constructor/base.py",
"repo_id": "langchain",
"token_count": 5442
} | 510 |
import pytest
from llama_index.legacy.storage.kvstore.firestore_kvstore import FirestoreKVStore
try:
from google.cloud import firestore_v1 as firestore
except ImportError:
firestore = None # type: ignore
@pytest.fixture()
def kvstore_with_data(firestore_kvstore: FirestoreKVStore) -> FirestoreKVStore:
te... | llama_index/llama-index-legacy/tests/storage/kvstore/test_firestore_kvstore.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/storage/kvstore/test_firestore_kvstore.py",
"repo_id": "llama_index",
"token_count": 740
} | 1,820 |
{
"redirects": [
{
"source": "/docs/integrations/llms/watsonxllm",
"destination": "/docs/integrations/llms/ibm_watsonx"
},
{
"source": "/docs/integrations/llms/pai_eas_endpoint",
"destination": "/docs/integrations/llms/alibabacloud_pai_eas_endpoint"
},
{
"source": "/d... | langchain/docs/vercel.json/0 | {
"file_path": "langchain/docs/vercel.json",
"repo_id": "langchain",
"token_count": 57310
} | 196 |
# Minimax
The `MinimaxEmbeddings` class uses the Minimax API to generate embeddings for a given text.
# Setup
To use Minimax model, you'll need a [Minimax account](https://api.minimax.chat), an [API key](https://api.minimax.chat/user-center/basic-information/interface-key), and a [Group ID](https://api.minimax.chat/... | langchainjs/docs/core_docs/docs/integrations/text_embedding/minimax.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/text_embedding/minimax.mdx",
"repo_id": "langchainjs",
"token_count": 263
} | 738 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team, The Microsoft Research team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | transformers/tests/models/prophetnet/test_tokenization_prophetnet.py/0 | {
"file_path": "transformers/tests/models/prophetnet/test_tokenization_prophetnet.py",
"repo_id": "transformers",
"token_count": 3445
} | 833 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import onnx_graphsurgeon as gs
import torch
from onnx import shape_inference
from packaging import version
from polygraphy.backend.onnx.loader import fold_constants
from torch.onnx import export
from diffusers import (
ControlNetModel,
... | diffusers/scripts/convert_stable_diffusion_controlnet_to_onnx.py/0 | {
"file_path": "diffusers/scripts/convert_stable_diffusion_controlnet_to_onnx.py",
"repo_id": "diffusers",
"token_count": 8995
} | 236 |
<jupyter_start><jupyter_text>Evaluate a Conversational Chat Bot[](https://colab.research.google.com/github/langchain-ai/langsmith-cookbook/blob/main/testing-examples/chat-single-turn/chat_evaluation_single_turn.ipynb)Chat bots, designed to assist users or provide entertainment, typically engage in multiple conversation... | langsmith-cookbook/testing-examples/chat-single-turn/chat_evaluation_single_turn.ipynb/0 | {
"file_path": "langsmith-cookbook/testing-examples/chat-single-turn/chat_evaluation_single_turn.ipynb",
"repo_id": "langsmith-cookbook",
"token_count": 3654
} | 1,062 |
import { describe, test } from "@jest/globals";
import { ChatMessage, HumanMessage } from "@langchain/core/messages";
import {
PromptTemplate,
ChatPromptTemplate,
AIMessagePromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
} from "@langchain/core/prompts";
import { getEnvironmentVariable... | langchainjs/libs/langchain-cloudflare/src/tests/chat_models.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-cloudflare/src/tests/chat_models.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1532
} | 957 |
from langchain_community.utilities.brave_search import BraveSearchWrapper
__all__ = ["BraveSearchWrapper"]
| langchain/libs/langchain/langchain/utilities/brave_search.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utilities/brave_search.py",
"repo_id": "langchain",
"token_count": 31
} | 573 |
import pytest
from typing import List
from llama_index.core.base.llms.types import ChatMessage, MessageRole
from llama_index.core.bridge.pydantic import BaseModel
from llama_index.llms.openai.utils import (
from_openai_message_dicts,
from_openai_messages,
to_openai_message_dicts,
to_openai_tool,
)
fr... | llama_index/llama-index-integrations/llms/llama-index-llms-openai/tests/test_openai_utils.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-openai/tests/test_openai_utils.py",
"repo_id": "llama_index",
"token_count": 3185
} | 1,324 |
import logging
import os
from pathlib import Path
import orjson
from fastapi import FastAPI, Form, UploadFile
from fastapi.staticfiles import StaticFiles
from app.api import router as api_router
from app.upload import ingest_runnable
logger = logging.getLogger(__name__)
app = FastAPI(title="OpenGPTs API")
# Get r... | opengpts/backend/app/server.py/0 | {
"file_path": "opengpts/backend/app/server.py",
"repo_id": "opengpts",
"token_count": 350
} | 2,055 |
from __future__ import annotations
import contextlib
import enum
import logging
import uuid
from typing import (
Any,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
Tuple,
Type,
)
import numpy as np
import sqlalchemy
from sqlalchemy import delete
from sqlalchemy.dialects.post... | langchain/libs/community/langchain_community/vectorstores/pgvector.py/0 | {
"file_path": "langchain/libs/community/langchain_community/vectorstores/pgvector.py",
"repo_id": "langchain",
"token_count": 16872
} | 339 |
---
hide_table_of_contents: true
---
# MultiQuery Retriever
Distance-based vector database retrieval embeds (represents) queries in high-dimensional space and finds similar embedded documents based on "distance".
But retrieval may produce different results with subtle changes in query wording or if the embeddings do ... | langchainjs/docs/core_docs/docs/modules/data_connection/retrievers/multi-query-retriever.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/data_connection/retrievers/multi-query-retriever.mdx",
"repo_id": "langchainjs",
"token_count": 416
} | 810 |
/* eslint-disable no-process-env */
import { test } from "@jest/globals";
import { Document } from "@langchain/core/documents";
import { OpenAI } from "@langchain/openai";
import { VectaraStore } from "@langchain/community/vectorstores/vectara";
import { FakeEmbeddings } from "@langchain/core/utils/testing";
import { A... | langchainjs/langchain/src/retrievers/self_query/tests/vectara_self_query.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/retrievers/self_query/tests/vectara_self_query.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1318
} | 961 |
<jupyter_start><jupyter_text>Jina Embeddings If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-embeddings-jinaai
%pip install llama-index-llms-openai
!pip install llama-index<jupyter_output><empty_output><jupyter_text>You may also need other... | llama_index/docs/examples/embeddings/jinaai_embeddings.ipynb/0 | {
"file_path": "llama_index/docs/examples/embeddings/jinaai_embeddings.ipynb",
"repo_id": "llama_index",
"token_count": 1278
} | 1,134 |
from llama_index.tools.yelp.base import YelpToolSpec
__all__ = ["YelpToolSpec"]
| llama_index/llama-index-integrations/tools/llama-index-tools-yelp/llama_index/tools/yelp/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-yelp/llama_index/tools/yelp/__init__.py",
"repo_id": "llama_index",
"token_count": 31
} | 1,505 |
from langchain_community.document_loaders.ifixit import IFixitLoader
__all__ = ["IFixitLoader"]
| langchain/libs/langchain/langchain/document_loaders/ifixit.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/ifixit.py",
"repo_id": "langchain",
"token_count": 31
} | 508 |
# Introduction [[introduction]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit6/thumbnail.png" alt="thumbnail"/>
In the last unit, we learned about Deep Q-Learning. In this value-based deep reinforcement learning algorithm, we **used a deep neural network to ... | deep-rl-class/units/en/unit4/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit4/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 462
} | 165 |
// 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/core/src/common/Slice.cpp/0 | {
"file_path": "milvus/internal/core/src/common/Slice.cpp",
"repo_id": "milvus",
"token_count": 1716
} | 1,864 |
# this is a demo of inference of IDEFICS-9B which needs about 20GB of GPU memory
import torch
from transformers import IdeficsForVisionText2Text, AutoProcessor
device = "cuda" if torch.cuda.is_available() else "cpu"
checkpoint = "HuggingFaceM4/idefics-9b"
#checkpoint = "HuggingFaceM4/tiny-random-idefics"
model = Id... | notebooks/examples/idefics/inference.py/0 | {
"file_path": "notebooks/examples/idefics/inference.py",
"repo_id": "notebooks",
"token_count": 980
} | 292 |
<jupyter_start><jupyter_text>Natural Language APIs`Natural Language API` Toolkits (`NLAToolkits`) permit LangChain Agents to efficiently plan and combine calls across endpoints. This notebook demonstrates a sample composition of the `Speak`, `Klarna`, and `Spoonacluar` APIs. First, import dependencies and load the LLM<... | langchain/docs/docs/integrations/toolkits/openapi_nla.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/toolkits/openapi_nla.ipynb",
"repo_id": "langchain",
"token_count": 2028
} | 169 |
"""Contains utilities to flag a feature as "experimental" in datasets."""
import warnings
from functools import wraps
from typing import Callable
def experimental(fn: Callable) -> Callable:
"""Decorator to flag a feature as experimental.
An experimental feature trigger a warning when used as it might be subj... | datasets/src/datasets/utils/experimental.py/0 | {
"file_path": "datasets/src/datasets/utils/experimental.py",
"repo_id": "datasets",
"token_count": 385
} | 135 |
/*
* 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/mq/msgstream/msg_for_partition.go/0 | {
"file_path": "milvus/pkg/mq/msgstream/msg_for_partition.go",
"repo_id": "milvus",
"token_count": 1201
} | 1,902 |
from .. import normalizers
Normalizer = normalizers.Normalizer
BertNormalizer = normalizers.BertNormalizer
NFD = normalizers.NFD
NFKD = normalizers.NFKD
NFC = normalizers.NFC
NFKC = normalizers.NFKC
Sequence = normalizers.Sequence
Lowercase = normalizers.Lowercase
Prepend = normalizers.Prepend
Strip = normalizers.Str... | tokenizers/bindings/python/py_src/tokenizers/normalizers/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/normalizers/__init__.py",
"repo_id": "tokenizers",
"token_count": 295
} | 436 |
<jupyter_start><jupyter_text>FallbacksWhen working with language models, you may often encounter issues from the underlying APIs, whether these be rate limiting or downtime. Therefore, as you go to move your LLM applications into production it becomes more and more important to safeguard against these. That's why we've... | langchain/docs/docs/guides/fallbacks.ipynb/0 | {
"file_path": "langchain/docs/docs/guides/fallbacks.ipynb",
"repo_id": "langchain",
"token_count": 2398
} | 90 |
import { test } from "@jest/globals";
import { OpenAI } from "@langchain/openai";
import { loadQueryConstructorChain } from "../index.js";
import {
Comparators,
Comparison,
Operation,
Operators,
StructuredQuery,
} from "../ir.js";
import { AttributeInfo } from "../../../schema/query_constructor.js";
import { ... | langchainjs/langchain/src/chains/query_constructor/tests/query_chain.int.test.ts/0 | {
"file_path": "langchainjs/langchain/src/chains/query_constructor/tests/query_chain.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1390
} | 957 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-elasticsearch/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-elasticsearch/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,429 |
# 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 applicabl... | accelerate/src/accelerate/utils/fsdp_utils.py/0 | {
"file_path": "accelerate/src/accelerate/utils/fsdp_utils.py",
"repo_id": "accelerate",
"token_count": 4830
} | 16 |
<!--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/en/model_doc/xlnet.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/xlnet.md",
"repo_id": "transformers",
"token_count": 2042
} | 498 |
#!/usr/bin/env python
"""Example LangChain server exposes and agent that has conversation history.
In this example, the history is stored entirely on the client's side.
Please see other examples in LangServe on how to use RunnableWithHistory to
store history on the server side.
Relevant LangChain documentation:
* C... | langserve/examples/agent_with_history/server.py/0 | {
"file_path": "langserve/examples/agent_with_history/server.py",
"repo_id": "langserve",
"token_count": 1895
} | 1,040 |
from __future__ import annotations
import logging
import os
import sys
import warnings
from typing import (
AbstractSet,
Any,
AsyncIterator,
Callable,
Collection,
Dict,
Iterator,
List,
Literal,
Mapping,
Optional,
Set,
Tuple,
Union,
)
from langchain_core._api.dep... | langchain/libs/community/langchain_community/llms/openai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/llms/openai.py",
"repo_id": "langchain",
"token_count": 22079
} | 280 |
from langchain_community.graphs.graph_store import GraphStore
__all__ = ["GraphStore"]
| langchain/libs/langchain/langchain/graphs/graph_store.py/0 | {
"file_path": "langchain/libs/langchain/langchain/graphs/graph_store.py",
"repo_id": "langchain",
"token_count": 26
} | 540 |
export * from "./base.js";
export * from "./bytes.js";
export * from "./list.js";
export * from "./string.js";
export * from "./transform.js";
export * from "./json.js";
export * from "./xml.js";
| langchainjs/langchain-core/src/output_parsers/index.ts/0 | {
"file_path": "langchainjs/langchain-core/src/output_parsers/index.ts",
"repo_id": "langchainjs",
"token_count": 70
} | 827 |
import type { Conversation } from "$lib/types/Conversation";
import type { Message } from "$lib/types/Message";
export function addSibling(
conv: Pick<Conversation, "messages" | "rootMessageId">,
message: Omit<Message, "id">,
siblingId: Message["id"]
): Message["id"] {
if (conv.messages.length === 0) {
throw new... | chat-ui/src/lib/utils/tree/addSibling.ts/0 | {
"file_path": "chat-ui/src/lib/utils/tree/addSibling.ts",
"repo_id": "chat-ui",
"token_count": 431
} | 114 |
from typing import List, Type
from langchain_core.tools import BaseTool, StructuredTool
import langchain_community.tools
from langchain_community.tools import _DEPRECATED_TOOLS
from langchain_community.tools import __all__ as tools_all
_EXCLUDE = {
BaseTool,
StructuredTool,
}
def _get_tool_classes(skip_too... | langchain/libs/community/tests/unit_tests/tools/test_exported.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/tools/test_exported.py",
"repo_id": "langchain",
"token_count": 584
} | 382 |
# langchain-ai21
This package contains the LangChain integrations for [AI21](https://docs.ai21.com/) through their [AI21](https://pypi.org/project/ai21/) SDK.
## Installation and Setup
- Install the AI21 partner package
```bash
pip install langchain-ai21
```
- Get an AI21 api key and set it as an environment variabl... | langchain/libs/partners/ai21/README.md/0 | {
"file_path": "langchain/libs/partners/ai21/README.md",
"repo_id": "langchain",
"token_count": 527
} | 612 |
# Salesforce Tool
This tool connects to a Salesforce environment and allow the Agent to perform SOQL and SOSL queries.
## Usage
This tool is a wrapper tool using the simple salesforce library. More information on this library [here](https://simple-salesforce.readthedocs.io/)
Here's an example usage of the Salesforc... | llama_index/llama-index-integrations/tools/llama-index-tools-salesforce/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-salesforce/README.md",
"repo_id": "llama_index",
"token_count": 434
} | 1,497 |
"""Azure Storage Blob file and directory reader.
A loader that fetches a file or iterates through a directory from Azure Storage Blob.
"""
import logging
import math
import os
import tempfile
import time
from typing import Any, Dict, List, Optional, Union
from azure.storage.blob import ContainerClient
from llama_ind... | llama_index/llama-index-integrations/readers/llama-index-readers-azstorage-blob/llama_index/readers/azstorage_blob/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-azstorage-blob/llama_index/readers/azstorage_blob/base.py",
"repo_id": "llama_index",
"token_count": 3534
} | 1,339 |
# candle-quantized-t5
## Seq2Seq example
This example uses a quantized version of the t5 model.
```bash
$ cargo run --example quantized-t5 --release -- --prompt "translate to German: A beautiful candle."
...
Eine schöne Kerze.
```
## Generating Quantized weight files
The weight file is automatically retrieved fro... | candle/candle-examples/examples/quantized-t5/README.md/0 | {
"file_path": "candle/candle-examples/examples/quantized-t5/README.md",
"repo_id": "candle",
"token_count": 683
} | 41 |
<!--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/en/model_doc/mt5.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/mt5.md",
"repo_id": "transformers",
"token_count": 1400
} | 512 |
def test_import() -> None:
from langchain_community.graphs import (
NeptuneGraph, # noqa: F401
NeptuneRdfGraph, # noqa: F401
)
| langchain/libs/community/tests/unit_tests/graphs/test_neptune_graph.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/graphs/test_neptune_graph.py",
"repo_id": "langchain",
"token_count": 66
} | 375 |
import json
import urllib.request
from base64 import b64encode
from typing import List, Optional
from langchain_core.documents import Document
from langchain_core.utils import get_from_env, stringify_value
from langchain_community.document_loaders.base import BaseLoader
MODERN_TREASURY_ENDPOINTS = {
"payment_ord... | langchain/libs/community/langchain_community/document_loaders/modern_treasury.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/modern_treasury.py",
"repo_id": "langchain",
"token_count": 1253
} | 254 |
# Data Coordinator
Data cooridnator(datacoord for short) is the component to organize DataNodes and segments allocations.
## Dependency
- KV store: a kv store has all the meta info datacoord needs to operate. (etcd)
- Message stream: a message stream to communicate statistics information with data nodes. (Pulsar)
- ... | milvus/internal/datacoord/README.md/0 | {
"file_path": "milvus/internal/datacoord/README.md",
"repo_id": "milvus",
"token_count": 119
} | 1,823 |
# LLMCompiler Agent Pack
This LlamaPack implements the [LLMCompiler agent paper](https://github.com/SqueezeAILab/LLMCompiler).
A lot of code came from the source repo, we repurposed with LlamaIndex abstractions. All credits
to the original authors for a great work!
A full notebook guide can be found [here](https://g... | llama_index/llama-index-packs/llama-index-packs-agents-llm-compiler/README.md/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-agents-llm-compiler/README.md",
"repo_id": "llama_index",
"token_count": 697
} | 1,828 |
python_sources()
| llama_index/llama-index-integrations/llms/llama-index-llms-litellm/llama_index/llms/litellm/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-litellm/llama_index/llms/litellm/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,228 |
# @langchain/azure-openai
This package contains the Azure SDK for OpenAI LangChain.js integrations.
It provides Azure OpenAI support through the [Azure SDK for OpenAI](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai) library.
## Installation
```bash npm2yarn
npm install @langchain/azure-opena... | langchainjs/libs/langchain-azure-openai/README.md/0 | {
"file_path": "langchainjs/libs/langchain-azure-openai/README.md",
"repo_id": "langchainjs",
"token_count": 1390
} | 942 |
# 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 applicabl... | transformers/tests/models/sam/test_processor_sam.py/0 | {
"file_path": "transformers/tests/models/sam/test_processor_sam.py",
"repo_id": "transformers",
"token_count": 4944
} | 735 |
# coding=utf-8
# Copyright 2022 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... | transformers/tests/models/conditional_detr/test_image_processing_conditional_detr.py/0 | {
"file_path": "transformers/tests/models/conditional_detr/test_image_processing_conditional_detr.py",
"repo_id": "transformers",
"token_count": 10681
} | 776 |
<jupyter_start><jupyter_text>ArangoDB QA chain[](https://colab.research.google.com/github/arangodb/interactive_tutorials/blob/master/notebooks/Langchain.ipynb)This notebook shows how to use LLMs to provide a natural language interface to an [ArangoDB](https://github.com/arangodb/arangodbreadme) database. You can get a ... | langchain/docs/docs/use_cases/graph/graph_arangodb_qa.ipynb/0 | {
"file_path": "langchain/docs/docs/use_cases/graph/graph_arangodb_qa.ipynb",
"repo_id": "langchain",
"token_count": 3061
} | 209 |
package iterator
import (
"github.com/cockroachdb/errors"
"github.com/milvus-io/milvus/internal/storage"
"github.com/milvus-io/milvus/pkg/util/typeutil"
)
var (
// ErrNoMoreRecord is the error that the iterator does not have next record.
ErrNoMoreRecord = errors.New("no more record")
// ErrDisposed is the erro... | milvus/internal/datanode/iterators/iterator.go/0 | {
"file_path": "milvus/internal/datanode/iterators/iterator.go",
"repo_id": "milvus",
"token_count": 638
} | 1,787 |
import glob
import os
import re
import shutil
from pathlib import Path
TEMPLATES_DIR = Path(os.path.abspath(__file__)).parents[2] / "templates"
DOCS_TEMPLATES_DIR = Path(os.path.abspath(__file__)).parents[1] / "docs" / "templates"
readmes = list(glob.glob(str(TEMPLATES_DIR) + "/*/README.md"))
destinations = [readme[... | langchain/docs/scripts/copy_templates.py/0 | {
"file_path": "langchain/docs/scripts/copy_templates.py",
"repo_id": "langchain",
"token_count": 458
} | 205 |
python_tests()
| llama_index/llama-index-integrations/callbacks/llama-index-callbacks-aim/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/callbacks/llama-index-callbacks-aim/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,207 |
python_tests()
| llama_index/llama-index-integrations/readers/llama-index-readers-wordlift/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-wordlift/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,474 |
# coding=utf-8
# Copyright 2019 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... | transformers/tests/utils/test_model_card.py/0 | {
"file_path": "transformers/tests/utils/test_model_card.py",
"repo_id": "transformers",
"token_count": 1475
} | 796 |
from langchain import docstore
from tests.unit_tests import assert_all_importable
EXPECTED_ALL = ["DocstoreFn", "InMemoryDocstore", "Wikipedia"]
def test_all_imports() -> None:
assert set(docstore.__all__) == set(EXPECTED_ALL)
assert_all_importable(docstore)
| langchain/libs/langchain/tests/unit_tests/docstore/test_imports.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/docstore/test_imports.py",
"repo_id": "langchain",
"token_count": 94
} | 599 |
python_sources()
| llama_index/llama-index-core/llama_index/core/indices/common_tree/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/common_tree/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,214 |
<jupyter_start><jupyter_text>Sentence Embedding Optimizer<jupyter_code>%pip install llama-index-readers-wikipedia
# My OpenAI Key
import os
os.environ["OPENAI_API_KEY"] = "INSERT OPENAI KEY"<jupyter_output><empty_output><jupyter_text>Setup If you're opening this Notebook on colab, you will probably need to install Lla... | llama_index/docs/examples/node_postprocessor/OptimizerDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/node_postprocessor/OptimizerDemo.ipynb",
"repo_id": "llama_index",
"token_count": 649
} | 1,118 |
import pytest
@pytest.fixture(scope="module")
def fused_kernel_mamba_handle(launcher):
with launcher("state-spaces/mamba-130m", num_shard=1) as handle:
yield handle
@pytest.fixture(scope="module")
async def fused_kernel_mamba(fused_kernel_mamba_handle):
await fused_kernel_mamba_handle.health(300)
... | text-generation-inference/integration-tests/models/test_mamba.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_mamba.py",
"repo_id": "text-generation-inference",
"token_count": 792
} | 382 |
import torch
import torch.distributed
from typing import Optional
from transformers import (
AutoTokenizer,
AutoConfig,
)
from text_generation_server.models import CausalLM
from text_generation_server.models.custom_modeling.neox_modeling import (
GPTNeoxForCausalLM,
)
from text_generation_server.utils imp... | text-generation-inference/server/text_generation_server/models/gpt_neox.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/gpt_neox.py",
"repo_id": "text-generation-inference",
"token_count": 1220
} | 425 |
"""Power BI agent."""
| langchain/libs/langchain/langchain/agents/agent_toolkits/powerbi/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/agents/agent_toolkits/powerbi/__init__.py",
"repo_id": "langchain",
"token_count": 7
} | 437 |
# @langchain/yandex
This package contains the LangChain.js integrations for YandexGPT through their [Foundation Models REST API](https://cloud.yandex.ru/en/docs/yandexgpt/api-ref/v1/).
## Installation
```bash npm2yarn
npm install @langchain/yandex
```
## Setup your environment
First, you should [create a service ac... | langchainjs/libs/langchain-yandex/README.md/0 | {
"file_path": "langchainjs/libs/langchain-yandex/README.md",
"repo_id": "langchainjs",
"token_count": 1106
} | 1,048 |
// 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/querycoordv2/utils/checker.go/0 | {
"file_path": "milvus/internal/querycoordv2/utils/checker.go",
"repo_id": "milvus",
"token_count": 780
} | 1,766 |
"""Test Anthropic Chat API wrapper."""
import os
from typing import List
import pytest
from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
from langchain_community.chat_models import ChatAnthropic
from langchain_community.chat_models.anthropic import (
convert_messages_to_promp... | langchain/libs/community/tests/unit_tests/chat_models/test_anthropic.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/chat_models/test_anthropic.py",
"repo_id": "langchain",
"token_count": 901
} | 367 |
use candle_wasm_example_whisper::worker::{Decoder as D, ModelData};
use wasm_bindgen::prelude::*;
#[wasm_bindgen]
pub struct Decoder {
decoder: D,
}
#[wasm_bindgen]
impl Decoder {
#[wasm_bindgen(constructor)]
#[allow(clippy::too_many_arguments)]
pub fn new(
weights: Vec<u8>,
tokenizer:... | candle/candle-wasm-examples/whisper/src/bin/m.rs/0 | {
"file_path": "candle/candle-wasm-examples/whisper/src/bin/m.rs",
"repo_id": "candle",
"token_count": 694
} | 80 |
<jupyter_start><jupyter_text>Database Reader If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.<jupyter_code>%pip install llama-index-readers-database
!pip install llama-index
import logging
import sys
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logging.getLogger(... | llama_index/docs/examples/data_connectors/DatabaseReaderDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/data_connectors/DatabaseReaderDemo.ipynb",
"repo_id": "llama_index",
"token_count": 985
} | 1,073 |
import { SingleStoreVectorStore } from "@langchain/community/vectorstores/singlestore";
import { OpenAIEmbeddings } from "@langchain/openai";
export const run = async () => {
const vectorStore = await SingleStoreVectorStore.fromTexts(
["Good afternoon", "Bye bye", "Boa tarde!", "Até logo!"],
[
{ id: 1,... | langchainjs/examples/src/indexes/vector_stores/singlestore_with_metadata_filter.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/singlestore_with_metadata_filter.ts",
"repo_id": "langchainjs",
"token_count": 407
} | 790 |
from llama_index.llms.replicate.base import Replicate
__all__ = ["Replicate"]
| llama_index/llama-index-integrations/llms/llama-index-llms-replicate/llama_index/llms/replicate/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-replicate/llama_index/llms/replicate/__init__.py",
"repo_id": "llama_index",
"token_count": 27
} | 1,244 |
from llama_index.vector_stores.metal.base import MetalVectorStore
__all__ = ["MetalVectorStore"]
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-metal/llama_index/vector_stores/metal/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-metal/llama_index/vector_stores/metal/__init__.py",
"repo_id": "llama_index",
"token_count": 29
} | 1,662 |
import inspect
import os
import random
import shutil
import tempfile
import weakref
from functools import wraps
from pathlib import Path
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import xxhash
from . import config
from .naming import INVALID_WINDOWS_CHARACT... | datasets/src/datasets/fingerprint.py/0 | {
"file_path": "datasets/src/datasets/fingerprint.py",
"repo_id": "datasets",
"token_count": 8037
} | 137 |
import inspect
from itertools import repeat
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...image_processor import VaeImageProcessor
from ...models import AutoencoderKL, UNet2DConditionModel
from ...pipelines.stable_diff... | diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 17978
} | 252 |
# `tokenizers-win32-x64-msvc`
This is the **x86_64-pc-windows-msvc** binary for `tokenizers`
| tokenizers/bindings/node/npm/win32-x64-msvc/README.md/0 | {
"file_path": "tokenizers/bindings/node/npm/win32-x64-msvc/README.md",
"repo_id": "tokenizers",
"token_count": 39
} | 430 |
// 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/datanode/allocator/allocator_test.go/0 | {
"file_path": "milvus/internal/datanode/allocator/allocator_test.go",
"repo_id": "milvus",
"token_count": 893
} | 1,798 |
import { Readability } from "@mozilla/readability";
import { JSDOM } from "jsdom";
import type { Options } from "mozilla-readability";
import {
MappingDocumentTransformer,
Document,
} from "@langchain/core/documents";
/**
* A transformer that uses the Mozilla Readability library to extract the
* main content fro... | langchainjs/libs/langchain-community/src/document_transformers/mozilla_readability.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/document_transformers/mozilla_readability.ts",
"repo_id": "langchainjs",
"token_count": 452
} | 952 |
---
title: Indexing
sidebar_position: 5
---
# Indexing
Here, we will look at a basic indexing workflow using the LangChain indexing API.
The indexing API lets you load and keep in sync documents from any source into a vector store. Specifically, it helps:
- Avoid writing duplicated content into the vector store
- A... | langchainjs/docs/core_docs/docs/modules/data_connection/indexing/index.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/data_connection/indexing/index.mdx",
"repo_id": "langchainjs",
"token_count": 1631
} | 741 |
# coding=utf-8
# Copyright 2022 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/.circleci/create_circleci_config.py/0 | {
"file_path": "transformers/.circleci/create_circleci_config.py",
"repo_id": "transformers",
"token_count": 12927
} | 484 |
python_tests()
| llama_index/llama-index-integrations/tools/llama-index-tools-openai/tests/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-openai/tests/BUILD",
"repo_id": "llama_index",
"token_count": 5
} | 1,489 |
<jupyter_start><jupyter_text>Airbyte SQL Index GuideWe will show how to generate SQL queries on a Snowflake db generated by Airbyte.<jupyter_code># Uncomment to enable debugging.
# import logging
# import sys
# logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
# logging.getLogger().addHandler(logging.Stream... | llama_index/docs/understanding/putting_it_all_together/structured_data/Airbyte_demo.ipynb/0 | {
"file_path": "llama_index/docs/understanding/putting_it_all_together/structured_data/Airbyte_demo.ipynb",
"repo_id": "llama_index",
"token_count": 2262
} | 1,131 |
from llama_index.readers.notion.base import NotionPageReader
__all__ = ["NotionPageReader"]
| llama_index/llama-index-integrations/readers/llama-index-readers-notion/llama_index/readers/notion/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-notion/llama_index/readers/notion/__init__.py",
"repo_id": "llama_index",
"token_count": 31
} | 1,491 |
from langchain_community.embeddings.databricks import DatabricksEmbeddings
__all__ = ["DatabricksEmbeddings"]
| langchain/libs/langchain/langchain/embeddings/databricks.py/0 | {
"file_path": "langchain/libs/langchain/langchain/embeddings/databricks.py",
"repo_id": "langchain",
"token_count": 35
} | 522 |
<jupyter_start><jupyter_text>EverNote>[EverNote](https://evernote.com/) is intended for archiving and creating notes in which photos, audio and saved web content can be embedded. Notes are stored in virtual "notebooks" and can be tagged, annotated, edited, searched, and exported.This notebook shows how to load an `Ever... | langchain/docs/docs/integrations/document_loaders/evernote.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/evernote.ipynb",
"repo_id": "langchain",
"token_count": 303
} | 106 |
python_sources()
| llama_index/llama-index-integrations/tools/llama-index-tools-azure-cv/llama_index/tools/azure_cv/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-azure-cv/llama_index/tools/azure_cv/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,472 |
from langchain_community.utilities.google_finance import GoogleFinanceAPIWrapper
__all__ = ["GoogleFinanceAPIWrapper"]
| langchain/libs/langchain/langchain/utilities/google_finance.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utilities/google_finance.py",
"repo_id": "langchain",
"token_count": 35
} | 574 |
"""Pinecone reader."""
from typing import Any, Dict, List, Optional
from llama_index.core.readers.base import BaseReader
from llama_index.core.schema import Document
class ZepReader(BaseReader):
"""Zep document vector store reader.
Args:
api_url (str): Zep API URL
api_key (str): Zep API key... | llama_index/llama-index-integrations/readers/llama-index-readers-zep/llama_index/readers/zep/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zep/llama_index/readers/zep/base.py",
"repo_id": "llama_index",
"token_count": 1081
} | 1,404 |
from typing import Any, Callable, List, NamedTuple, Union
import pytest
from langchain_core.beta.runnables.context import Context
from langchain_core.output_parsers.string import StrOutputParser
from langchain_core.prompt_values import StringPromptValue
from langchain_core.prompts.prompt import PromptTemplate
from la... | langchain/libs/core/tests/unit_tests/runnables/test_context.py/0 | {
"file_path": "langchain/libs/core/tests/unit_tests/runnables/test_context.py",
"repo_id": "langchain",
"token_count": 6581
} | 410 |
from langchain_openai.llms.azure import AzureOpenAI
from langchain_openai.llms.base import OpenAI
__all__ = [
"OpenAI",
"AzureOpenAI",
]
| langchain/libs/partners/openai/langchain_openai/llms/__init__.py/0 | {
"file_path": "langchain/libs/partners/openai/langchain_openai/llms/__init__.py",
"repo_id": "langchain",
"token_count": 59
} | 675 |
// Code generated by mockery v2.32.4. DO NOT EDIT.
package mockrootcoord
import (
context "context"
model "github.com/milvus-io/milvus/internal/metastore/model"
mock "github.com/stretchr/testify/mock"
)
// GarbageCollector is an autogenerated mock type for the GarbageCollector type
type GarbageCollector struct {... | milvus/internal/rootcoord/mocks/garbage_collector.go/0 | {
"file_path": "milvus/internal/rootcoord/mocks/garbage_collector.go",
"repo_id": "milvus",
"token_count": 3643
} | 2,003 |
"""Base class for Slack tools."""
from __future__ import annotations
from typing import TYPE_CHECKING
from langchain_core.pydantic_v1 import Field
from langchain_core.tools import BaseTool
from langchain_community.tools.slack.utils import login
if TYPE_CHECKING:
from slack_sdk import WebClient
class SlackBase... | langchain/libs/community/langchain_community/tools/slack/base.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/slack/base.py",
"repo_id": "langchain",
"token_count": 139
} | 295 |
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ja/tasks/monocular_depth_estimation.md/0 | {
"file_path": "transformers/docs/source/ja/tasks/monocular_depth_estimation.md",
"repo_id": "transformers",
"token_count": 2274
} | 535 |
#include "cuda_fp16.h"
#include "cuda_bf16.h"
// Table showing which features are supported on which compute capability
// https://docs.nvidia.com/cuda/cuda-c-programming-guide/#features-and-technical-specifications
// FIXME: the minimum compute capabilities are just guesses since the table is not specific enough
#i... | candle/candle-kernels/src/compatibility.cuh/0 | {
"file_path": "candle/candle-kernels/src/compatibility.cuh",
"repo_id": "candle",
"token_count": 2734
} | 51 |
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