text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
""" Vision OutLOoker (VOLO) implementation
Paper: `VOLO: Vision Outlooker for Visual Recognition` - https://arxiv.org/abs/2106.13112
Code adapted from official impl at https://github.com/sail-sg/volo, original copyright in comment below
Modifications and additions for timm by / Copyright 2022, Ross Wightman
"""
# Co... | pytorch-image-models/timm/models/volo.py/0 | {
"file_path": "pytorch-image-models/timm/models/volo.py",
"repo_id": "pytorch-image-models",
"token_count": 15802
} | 384 |
use candle::{Result, Tensor};
/// The negative log likelihood loss.
///
/// Arguments
///
/// * [inp]: The input tensor of dimensions `N, C` where `N` is the batch size and `C` the number
/// of categories. This is expected to contain log probabilities.
/// * [target]: The ground truth labels as a tensor of u... | candle/candle-nn/src/loss.rs/0 | {
"file_path": "candle/candle-nn/src/loss.rs",
"repo_id": "candle",
"token_count": 1040
} | 63 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/trajectory_transformer.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/trajectory_transformer.md",
"repo_id": "transformers",
"token_count": 776
} | 471 |
---
hide_table_of_contents: true
---
# Subtitles
This example goes over how to load data from subtitle files. One document will be created for each subtitles file.
## Setup
```bash npm2yarn
npm install srt-parser-2
```
## Usage
```typescript
import { SRTLoader } from "langchain/document_loaders/fs/srt";
const lo... | langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/subtitles.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/document_loaders/file_loaders/subtitles.mdx",
"repo_id": "langchainjs",
"token_count": 171
} | 703 |
use crate::utils::SysRegex;
use serde::{Deserialize, Deserializer, Serialize};
use crate::tokenizer::{
pattern::Invert, PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior,
};
/// Represents the different patterns that `Split` can use
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Eq)]
pub... | tokenizers/tokenizers/src/pre_tokenizers/split.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/split.rs",
"repo_id": "tokenizers",
"token_count": 4038
} | 461 |
import { BufferMemory } from "langchain/memory";
import { RedisChatMessageHistory } from "@langchain/community/stores/message/ioredis";
import { ChatOpenAI } from "@langchain/openai";
import { ConversationChain } from "langchain/chains";
const memory = new BufferMemory({
chatHistory: new RedisChatMessageHistory({
... | langchainjs/examples/src/memory/redis.ts/0 | {
"file_path": "langchainjs/examples/src/memory/redis.ts",
"repo_id": "langchainjs",
"token_count": 352
} | 840 |
import os
import pytest
from langchain_core.messages import AIMessage, HumanMessage
from langchain_community.chat_message_histories import TiDBChatMessageHistory
try:
CONNECTION_STRING = os.getenv("TEST_TiDB_CHAT_URL", "")
if CONNECTION_STRING == "":
raise OSError("TEST_TiDB_URL environment variable... | langchain/libs/community/tests/integration_tests/chat_message_histories/test_tidb.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/chat_message_histories/test_tidb.py",
"repo_id": "langchain",
"token_count": 1452
} | 317 |
from llama_index.embeddings.nomic.base import NomicEmbedding
__all__ = ["NomicEmbedding"]
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-nomic/llama_index/embeddings/nomic/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-nomic/llama_index/embeddings/nomic/__init__.py",
"repo_id": "llama_index",
"token_count": 34
} | 1,321 |
# 🦜🍎️ LangChain Core
[](https://pepy.tech/project/langchain_core)
[](https://opensource.org/licenses/MIT)
## Quick Install
```bash
pip install langchain-core
```
## What is it?
Lan... | langchain/libs/core/README.md/0 | {
"file_path": "langchain/libs/core/README.md",
"repo_id": "langchain",
"token_count": 1348
} | 388 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/src/diffusers/pipelines/kandinsky/pipeline_kandinsky_combined.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky/pipeline_kandinsky_combined.py",
"repo_id": "diffusers",
"token_count": 16909
} | 226 |
from typing import Callable, Union
from langchain_core.documents import Document
from langchain_community.docstore.base import Docstore
class DocstoreFn(Docstore):
"""Langchain Docstore via arbitrary lookup function.
This is useful when:
* it's expensive to construct an InMemoryDocstore/dict
* yo... | langchain/libs/community/langchain_community/docstore/arbitrary_fn.py/0 | {
"file_path": "langchain/libs/community/langchain_community/docstore/arbitrary_fn.py",
"repo_id": "langchain",
"token_count": 422
} | 239 |
# Copyright 2024 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/quantizers/quantizer_gptq.py/0 | {
"file_path": "transformers/src/transformers/quantizers/quantizer_gptq.py",
"repo_id": "transformers",
"token_count": 1447
} | 689 |
import {check} from 'k6';
import http from 'k6/http';
import {Trend} from 'k6/metrics';
const host = __ENV.HOST || '127.0.0.1:3000';
const totalTime = new Trend('total_time', true);
const validationTime = new Trend('validation_time', true);
const queueTime = new Trend('queue_time', true);
const inferenceTime = new Tr... | text-generation-inference/load_tests/starcoder_load.js/0 | {
"file_path": "text-generation-inference/load_tests/starcoder_load.js",
"repo_id": "text-generation-inference",
"token_count": 835
} | 372 |
#include <metal_stdlib>
#include <metal_math>
#
using namespace metal;
METAL_FUNC uint get_strided_index(
uint idx,
constant size_t &num_dims,
constant size_t *dims,
constant size_t *strides
) {
uint strided_i = 0;
for (uint d = 0; d < num_dims; d++) {
uint dim_idx = num_dims - 1 - d;
... | candle/candle-metal-kernels/src/unary.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/unary.metal",
"repo_id": "candle",
"token_count": 1956
} | 55 |
# The Deep Q-Network (DQN) [[deep-q-network]]
This is the architecture of our Deep Q-Learning network:
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit4/deep-q-network.jpg" alt="Deep Q Network"/>
As input, we take a **stack of 4 frames** passed through the netwo... | deep-rl-class/units/en/unit3/deep-q-network.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit3/deep-q-network.mdx",
"repo_id": "deep-rl-class",
"token_count": 888
} | 169 |
from threading import Thread
from typing import Any, Callable, Generator, Optional, Sequence
from llama_index.core.base.llms.types import (
ChatMessage,
ChatResponse,
ChatResponseAsyncGen,
ChatResponseGen,
CompletionResponse,
CompletionResponseAsyncGen,
CompletionResponseGen,
LLMMetadat... | llama_index/llama-index-integrations/llms/llama-index-llms-langchain/llama_index/llms/langchain/base.py/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-langchain/llama_index/llms/langchain/base.py",
"repo_id": "llama_index",
"token_count": 3417
} | 1,299 |
import random
import logging
# import math
from locust import TaskSet, task
from . import utils
logger = logging.getLogger("milvus_benchmark.runners.locust_tasks")
class Tasks(TaskSet):
@task
def query(self):
""" search interface """
op = "query"
# X = utils.generate_vectors(self.para... | milvus/tests/benchmark/milvus_benchmark/runners/locust_tasks.py/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/runners/locust_tasks.py",
"repo_id": "milvus",
"token_count": 1529
} | 2,080 |
"""Tool for the SceneXplain API."""
from typing import Optional
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import BaseTool
from langchain_community.utilities.scenexplain import SceneXplainAPIWrapper
class SceneXpla... | langchain/libs/community/langchain_community/tools/scenexplain/tool.py/0 | {
"file_path": "langchain/libs/community/langchain_community/tools/scenexplain/tool.py",
"repo_id": "langchain",
"token_count": 359
} | 307 |
// 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/util/importutil/import_wrapper_test.go/0 | {
"file_path": "milvus/internal/util/importutil/import_wrapper_test.go",
"repo_id": "milvus",
"token_count": 13832
} | 1,899 |
<jupyter_start><jupyter_text>WhatsAppThis notebook shows how to use the WhatsApp chat loader. This class helps map exported WhatsApp conversations to LangChain chat messages.The process has three steps:1. Export the chat conversations to computer2. Create the `WhatsAppChatLoader` with the file path pointed to the json ... | langchain/docs/docs/integrations/chat_loaders/whatsapp.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/chat_loaders/whatsapp.ipynb",
"repo_id": "langchain",
"token_count": 1083
} | 92 |
// 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/session/cluster.go/0 | {
"file_path": "milvus/internal/querycoordv2/session/cluster.go",
"repo_id": "milvus",
"token_count": 3971
} | 1,759 |
<!--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... | peft/docs/source/task_guides/ia3.md/0 | {
"file_path": "peft/docs/source/task_guides/ia3.md",
"repo_id": "peft",
"token_count": 3197
} | 296 |
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_TestCommandArgs = namedtuple(
"_TestCommandArgs",
[
"dataset",
"name",... | datasets/tests/commands/test_test.py/0 | {
"file_path": "datasets/tests/commands/test_test.py",
"repo_id": "datasets",
"token_count": 1511
} | 144 |
import { BaseLanguageModel } from "@langchain/core/language_models/base";
import { RunnableConfig } from "@langchain/core/runnables";
import { Example, Run } from "langsmith";
import { EvaluationResult, RunEvaluator } from "langsmith/evaluation";
import { Criteria as CriteriaType } from "../evaluation/index.js";
import... | langchainjs/langchain/src/smith/config.ts/0 | {
"file_path": "langchainjs/langchain/src/smith/config.ts",
"repo_id": "langchainjs",
"token_count": 3331
} | 923 |
// 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/proxy/impl_test.go/0 | {
"file_path": "milvus/internal/proxy/impl_test.go",
"repo_id": "milvus",
"token_count": 20257
} | 1,738 |
from pathlib import Path
from typing import Dict
def find_and_replace(source: str, replacements: Dict[str, str]) -> str:
rtn = source
# replace keys in deterministic alphabetical order
finds = sorted(replacements.keys())
for find in finds:
replace = replacements[find]
rtn = rtn.replac... | langchain/libs/cli/langchain_cli/utils/find_replace.py/0 | {
"file_path": "langchain/libs/cli/langchain_cli/utils/find_replace.py",
"repo_id": "langchain",
"token_count": 331
} | 202 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-github/llama_index/readers/github/issues/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-github/llama_index/readers/github/issues/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,375 |
<jupyter_start><jupyter_text>Textual-inversion fine-tuning for Stable Diffusion using d🧨ffusers This notebook shows how to "teach" Stable Diffusion a new concept via textual-inversion using 🤗 Hugging Face [🧨 Diffusers library](https://github.com/huggingface/diffusers). _By using just 3-5 images you can teach new con... | notebooks/diffusers/sd_textual_inversion_training.ipynb/0 | {
"file_path": "notebooks/diffusers/sd_textual_inversion_training.ipynb",
"repo_id": "notebooks",
"token_count": 10904
} | 290 |
# Milvus Code Review Guide
All PRs are checked in automatically by the sre-robot, with the following conditions:
1. DCO check passed
2. All test passed and code coverage check passed, with a `ci-passed` label
- Notes: If there is a `[skip e2e]` tag in the commit message, it skips running e2e tests automatically,
... | milvus/CODE_REVIEW.md/0 | {
"file_path": "milvus/CODE_REVIEW.md",
"repo_id": "milvus",
"token_count": 857
} | 1,618 |
export * from "./chat_models.js";
export * from "./llms.js";
export * from "./auth.js";
export * from "./connection.js";
export * from "./types.js";
export * from "./utils/stream.js";
export * from "./utils/common.js";
| langchainjs/libs/langchain-google-common/src/index.ts/0 | {
"file_path": "langchainjs/libs/langchain-google-common/src/index.ts",
"repo_id": "langchainjs",
"token_count": 78
} | 1,015 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/manim_animations/big_model_inference/stage_4.py/0 | {
"file_path": "accelerate/manim_animations/big_model_inference/stage_4.py",
"repo_id": "accelerate",
"token_count": 2919
} | 8 |
<jupyter_start><jupyter_text>Returning Structured OutputThis notebook covers how to have an agent return a structured output.By default, most of the agents return a single string.It can often be useful to have an agent return something with more structure.A good example of this is an agent tasked with doing question-an... | langchain/docs/docs/modules/agents/how_to/agent_structured.ipynb/0 | {
"file_path": "langchain/docs/docs/modules/agents/how_to/agent_structured.ipynb",
"repo_id": "langchain",
"token_count": 2324
} | 188 |
python_sources()
| llama_index/llama-index-core/llama_index/core/query_engine/flare/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/query_engine/flare/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,135 |
python_sources()
| llama_index/llama-index-core/llama_index/core/query_engine/pandas/BUILD/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/query_engine/pandas/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,210 |
python_sources()
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-cohere/llama_index/embeddings/cohere/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,255 |
<!--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/en/using-diffusers/schedulers.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/schedulers.md",
"repo_id": "diffusers",
"token_count": 3997
} | 192 |
from langchain_community.utils.ernie_functions import (
FunctionDescription,
ToolDescription,
convert_pydantic_to_ernie_function,
convert_pydantic_to_ernie_tool,
)
__all__ = [
"FunctionDescription",
"ToolDescription",
"convert_pydantic_to_ernie_function",
"convert_pydantic_to_ernie_tool... | langchain/libs/langchain/langchain/utils/ernie_functions.py/0 | {
"file_path": "langchain/libs/langchain/langchain/utils/ernie_functions.py",
"repo_id": "langchain",
"token_count": 129
} | 609 |
<jupyter_start><jupyter_text>WordPiece tokenizationAucun modèle en français utilise WordPiece. Nous utilisons ici CamemBERT utilise SentencePiece. Installez les bibliothèques 🤗 *Transformers* et 🤗 *Datasets* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
corpus = [
"C'... | notebooks/course/fr/chapter6/section6.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter6/section6.ipynb",
"repo_id": "notebooks",
"token_count": 1867
} | 299 |
import { OpenAI } from "@langchain/openai";
import { LLMChain } from "langchain/chains";
import { PromptTemplate } from "@langchain/core/prompts";
// Create a new LLMChain from a PromptTemplate and an LLM in streaming mode.
const model = new OpenAI({ temperature: 0.9, streaming: true });
const prompt = PromptTemplate.... | langchainjs/examples/src/chains/llm_chain_cancellation.ts/0 | {
"file_path": "langchainjs/examples/src/chains/llm_chain_cancellation.ts",
"repo_id": "langchainjs",
"token_count": 317
} | 800 |
# candle-resnet
A candle implementation of inference using a pre-trained [ResNet](https://arxiv.org/abs/1512.03385).
This uses a classification head trained on the ImageNet dataset and returns the
probabilities for the top-5 classes.
## Running an example
```
$ cargo run --example resnet --release -- --image tiger.j... | candle/candle-examples/examples/resnet/README.md/0 | {
"file_path": "candle/candle-examples/examples/resnet/README.md",
"repo_id": "candle",
"token_count": 204
} | 45 |
mod health;
/// Text Generation Inference Webserver
mod infer;
mod queue;
pub mod server;
mod validation;
use infer::{Infer, InferError, InferStreamResponse};
use queue::{Entry, Queue};
use serde::{Deserialize, Serialize};
use tokio::sync::OwnedSemaphorePermit;
use tokio_stream::wrappers::UnboundedReceiverStream;
use ... | text-generation-inference/router/src/lib.rs/0 | {
"file_path": "text-generation-inference/router/src/lib.rs",
"repo_id": "text-generation-inference",
"token_count": 10761
} | 386 |
from langchain_community.llms.textgen import TextGen
__all__ = ["TextGen"]
| langchain/libs/langchain/langchain/llms/textgen.py/0 | {
"file_path": "langchain/libs/langchain/langchain/llms/textgen.py",
"repo_id": "langchain",
"token_count": 25
} | 516 |
# Text Generation Inference
Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation for the most popular open-source LLMs, including Llama, Falcon, StarCoder, BLOOM, GPT-NeoX, and T5.
![Text Generation Inference](https://hugging... | text-generation-inference/docs/source/index.md/0 | {
"file_path": "text-generation-inference/docs/source/index.md",
"repo_id": "text-generation-inference",
"token_count": 544
} | 390 |
python_tests(
name="tests",
)
| llama_index/llama-index-experimental/tests/param_tuner/BUILD/0 | {
"file_path": "llama_index/llama-index-experimental/tests/param_tuner/BUILD",
"repo_id": "llama_index",
"token_count": 15
} | 1,333 |
<jupyter_start><jupyter_text>Custom Cohere Reranker This notebook provides a tutorial on building the Cohere Custom Re-ranker using LlamaIndex abstractions. Upon completion, you'll be able to create a Custom re-ranker and utilize it for enhanced data retrieval.**Important:** This notebook offers a guide for Cohere Cust... | llama_index/docs/examples/finetuning/rerankers/cohere_custom_reranker.ipynb/0 | {
"file_path": "llama_index/docs/examples/finetuning/rerankers/cohere_custom_reranker.ipynb",
"repo_id": "llama_index",
"token_count": 5232
} | 1,121 |
"""Unit test for Google Trends API Wrapper."""
import os
from unittest.mock import patch
from langchain_community.utilities.google_trends import GoogleTrendsAPIWrapper
@patch("serpapi.SerpApiClient.get_json")
def test_unexpected_response(mocked_serpapiclient): # type: ignore[no-untyped-def]
os.environ["SERPAPI_... | langchain/libs/community/tests/integration_tests/utilities/test_google_trends.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/utilities/test_google_trends.py",
"repo_id": "langchain",
"token_count": 813
} | 366 |
// 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/storage/TencentCloudCredentialsProvider.cpp/0 | {
"file_path": "milvus/internal/core/src/storage/TencentCloudCredentialsProvider.cpp",
"repo_id": "milvus",
"token_count": 3250
} | 1,667 |
import argparse
import math
import os
import shlex
import subprocess
import uuid
from distutils.util import strtobool
import requests
def parse_args():
# fmt: off
parser = argparse.ArgumentParser()
parser.add_argument("--command", type=str, default="",
help="the command to run")
parser.add_ar... | trl/benchmark/benchmark.py/0 | {
"file_path": "trl/benchmark/benchmark.py",
"repo_id": "trl",
"token_count": 2824
} | 769 |
# Milvus 2.x vs. 1.x: Cloud-native, distributed architecture, highly scalable, and more
<table class="comparison">
<thead>
<tr>
<th> </th>
<th>Milvus 1.x</th>
<th>Milvus 2.x</th>
</tr>
<tr>
<th>Architecture</th>
<td>Shared storage</td>
<td>Cloud native</td>
</tr>
</thead>
<tbody>
<tr>
<th>Scala... | milvus/milvus20vs1x.md/0 | {
"file_path": "milvus/milvus20vs1x.md",
"repo_id": "milvus",
"token_count": 1713
} | 1,878 |
import { type ClientOptions } from "openai";
import { type BaseLLMParams } from "@langchain/core/language_models/llms";
import { OpenAI } from "../llms.js";
import type {
OpenAIInput,
AzureOpenAIInput,
LegacyOpenAIInput,
} from "../types.js";
export class AzureOpenAI extends OpenAI {
get lc_aliases(): Record<s... | langchainjs/libs/langchain-openai/src/azure/llms.ts/0 | {
"file_path": "langchainjs/libs/langchain-openai/src/azure/llms.ts",
"repo_id": "langchainjs",
"token_count": 809
} | 1,038 |
"""Loads data from OneDrive"""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Iterator, List, Optional, Sequence, Union
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import Field
from langchain_community.document_loaders.base_o365 import (
O365... | langchain/libs/community/langchain_community/document_loaders/onedrive.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/onedrive.py",
"repo_id": "langchain",
"token_count": 1369
} | 242 |
# Yelp Tool
This tool connects to Yelp and allows the Agent to search for business and fetch the reviews.
## Usage
This tool has more extensive example usage documented in a Jupyter notebook [here](https://github.com/emptycrown/llama-hub/tree/main/llama_hub/tools/notebooks/yelp.ipynb)
Here's an example usage of the... | llama_index/llama-index-integrations/tools/llama-index-tools-yelp/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-yelp/README.md",
"repo_id": "llama_index",
"token_count": 292
} | 1,642 |
"""Test MosaicML API wrapper."""
import re
import pytest
from langchain_community.llms.mosaicml import PROMPT_FOR_GENERATION_FORMAT, MosaicML
def test_mosaicml_llm_call() -> None:
"""Test valid call to MosaicML."""
llm = MosaicML(model_kwargs={})
output = llm("Say foo:")
assert isinstance(output, st... | langchain/libs/community/tests/integration_tests/llms/test_mosaicml.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/llms/test_mosaicml.py",
"repo_id": "langchain",
"token_count": 1070
} | 339 |
# 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/upernet/test_modeling_upernet.py/0 | {
"file_path": "transformers/tests/models/upernet/test_modeling_upernet.py",
"repo_id": "transformers",
"token_count": 4945
} | 775 |
poetry_requirements(
name="poetry",
)
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-ollama/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-ollama/BUILD",
"repo_id": "llama_index",
"token_count": 18
} | 1,370 |
"""**Prompt** is the input to the model.
Prompt is often constructed
from multiple components. Prompt classes and functions make constructing
and working with prompts easy.
**Class hierarchy:**
.. code-block::
BasePromptTemplate --> PipelinePromptTemplate
StringPromptTemplate --> Pro... | langchain/libs/langchain/langchain/prompts/__init__.py/0 | {
"file_path": "langchain/libs/langchain/langchain/prompts/__init__.py",
"repo_id": "langchain",
"token_count": 1126
} | 535 |
# coding=utf-8
# Copyright 2023 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/efficientnet/convert_efficientnet_to_pytorch.py/0 | {
"file_path": "transformers/src/transformers/models/efficientnet/convert_efficientnet_to_pytorch.py",
"repo_id": "transformers",
"token_count": 5603
} | 639 |
<jupyter_start><jupyter_text>BigQuery Vector Search> [**BigQuery Vector Search**](https://cloud.google.com/bigquery/docs/vector-search-intro) lets you use GoogleSQL to do semantic search, using vector indexes for fast approximate results, or using brute force for exact results.This tutorial illustrates how to work with... | langchain/docs/docs/integrations/vectorstores/bigquery_vector_search.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/bigquery_vector_search.ipynb",
"repo_id": "langchain",
"token_count": 1562
} | 174 |
poetry_requirements(
name="poetry",
)
python_requirements(
name="reqs",
)
| llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-zendesk/BUILD",
"repo_id": "llama_index",
"token_count": 36
} | 1,478 |
from tokenizers import Tokenizer
from tokenizers.models import BPE
from tokenizers.pre_tokenizers import Whitespace
from tokenizers.trainers import BpeTrainer
from ..utils import data_dir, doc_wiki_tokenizer
disable_printing = True
original_print = print
def print(*args, **kwargs):
if not disable_printing:
... | tokenizers/bindings/python/tests/documentation/test_quicktour.py/0 | {
"file_path": "tokenizers/bindings/python/tests/documentation/test_quicktour.py",
"repo_id": "tokenizers",
"token_count": 3324
} | 453 |
<!--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/camembert.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/camembert.md",
"repo_id": "transformers",
"token_count": 1309
} | 440 |
---
hide_table_of_contents: true
---
import CodeBlock from "@theme/CodeBlock";
# Web Browser Tool
The Webbrowser Tool gives your agent the ability to visit a website and extract information. It is described to the agent as
```
useful for when you need to find something on or summarize a webpage. input should be a c... | langchainjs/docs/core_docs/docs/integrations/tools/webbrowser.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/tools/webbrowser.mdx",
"repo_id": "langchainjs",
"token_count": 371
} | 740 |
label: "How to"
position: 4
| langchainjs/docs/core_docs/docs/expression_language/how_to/_category_.yml/0 | {
"file_path": "langchainjs/docs/core_docs/docs/expression_language/how_to/_category_.yml",
"repo_id": "langchainjs",
"token_count": 11
} | 717 |
import { expect, test } from "@jest/globals";
import chroma from "./initClient";
import { IncludeEnum } from "../src/types";
import { EMBEDDINGS, IDS, METADATAS, DOCUMENTS } from "./data";
import { IEmbeddingFunction } from "../src/embeddings/IEmbeddingFunction";
export class TestEmbeddingFunction implements IEmbeddi... | chroma/clients/js/test/query.collection.test.ts/0 | {
"file_path": "chroma/clients/js/test/query.collection.test.ts",
"repo_id": "chroma",
"token_count": 2058
} | 32 |
// 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/import_manager_test.go/0 | {
"file_path": "milvus/internal/rootcoord/import_manager_test.go",
"repo_id": "milvus",
"token_count": 15315
} | 1,920 |
// 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/metastore/kv/binlog/binlog_test.go/0 | {
"file_path": "milvus/internal/metastore/kv/binlog/binlog_test.go",
"repo_id": "milvus",
"token_count": 3538
} | 1,825 |
# LlamaIndex Embeddings Integration: Google
| llama_index/llama-index-integrations/embeddings/llama-index-embeddings-google/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/embeddings/llama-index-embeddings-google/README.md",
"repo_id": "llama_index",
"token_count": 11
} | 1,258 |
import { FaissStore } from "@langchain/community/vectorstores/faiss";
import { OpenAIEmbeddings } from "@langchain/openai";
import { TextLoader } from "langchain/document_loaders/fs/text";
// Create docs with a loader
const loader = new TextLoader("src/document_loaders/example_data/example.txt");
const docs = await lo... | langchainjs/examples/src/indexes/vector_stores/faiss_fromdocs.ts/0 | {
"file_path": "langchainjs/examples/src/indexes/vector_stores/faiss_fromdocs.ts",
"repo_id": "langchainjs",
"token_count": 172
} | 874 |
from langchain_community.callbacks.comet_ml_callback import (
CometCallbackHandler,
)
__all__ = [
"CometCallbackHandler",
]
| langchain/libs/langchain/langchain/callbacks/comet_ml_callback.py/0 | {
"file_path": "langchain/libs/langchain/langchain/callbacks/comet_ml_callback.py",
"repo_id": "langchain",
"token_count": 47
} | 456 |
""" RMSProp modified to behave like Tensorflow impl
Originally cut & paste from PyTorch RMSProp
https://github.com/pytorch/pytorch/blob/063946d2b3f3f1e953a2a3b54e0b34f1393de295/torch/optim/rmsprop.py
Licensed under BSD-Clause 3 (ish), https://github.com/pytorch/pytorch/blob/master/LICENSE
Modifications Copyright 2021... | pytorch-image-models/timm/optim/rmsprop_tf.py/0 | {
"file_path": "pytorch-image-models/timm/optim/rmsprop_tf.py",
"repo_id": "pytorch-image-models",
"token_count": 2901
} | 394 |
python_sources()
python_tests(
name="tests",
)
| llama_index/llama-index-core/tests/storage/index_store/BUILD/0 | {
"file_path": "llama_index/llama-index-core/tests/storage/index_store/BUILD",
"repo_id": "llama_index",
"token_count": 22
} | 1,215 |
from __future__ import print_function
import os
from kubernetes import client, config
from kubernetes.client.rest import ApiException
from utils.util_log import test_log as log
from common.common_type import in_cluster_env
_GROUP = 'milvus.io'
_VERSION = 'v1alpha1'
_NAMESPACE = "default"
class CustomResourceOperat... | milvus/tests/python_client/common/cus_resource_opts.py/0 | {
"file_path": "milvus/tests/python_client/common/cus_resource_opts.py",
"repo_id": "milvus",
"token_count": 2424
} | 2,177 |
import pathlib
from langchain_community.chat_loaders import slack, utils
def test_slack_chat_loader() -> None:
chat_path = pathlib.Path(__file__).parents[2] / "examples" / "slack_export.zip"
loader = slack.SlackChatLoader(str(chat_path))
chat_sessions = list(
utils.map_ai_messages(loader.lazy_lo... | langchain/libs/community/tests/unit_tests/chat_loaders/test_slack.py/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/chat_loaders/test_slack.py",
"repo_id": "langchain",
"token_count": 225
} | 366 |
from typing import List, Optional, Sequence
from llama_index.core.base.base_query_engine import BaseQueryEngine
from llama_index.core.base.response.schema import RESPONSE_TYPE
from llama_index.core.callbacks.base import CallbackManager
from llama_index.core.indices.query.query_transform.base import BaseQueryTransform
... | llama_index/llama-index-core/llama_index/core/query_engine/transform_query_engine.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/query_engine/transform_query_engine.py",
"repo_id": "llama_index",
"token_count": 1381
} | 1,197 |
module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
}
| langsmith-cookbook/feedback-examples/nextjs/postcss.config.js/0 | {
"file_path": "langsmith-cookbook/feedback-examples/nextjs/postcss.config.js",
"repo_id": "langsmith-cookbook",
"token_count": 38
} | 1,056 |
# 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/stable_diffusion_2/test_stable_diffusion_latent_upscale.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_latent_upscale.py",
"repo_id": "diffusers",
"token_count": 4989
} | 290 |
<!---
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 ... | transformers/examples/tensorflow/contrastive-image-text/README.md/0 | {
"file_path": "transformers/examples/tensorflow/contrastive-image-text/README.md",
"repo_id": "transformers",
"token_count": 1054
} | 609 |
# LlamaIndex Llms Integration: Vertex
| llama_index/llama-index-integrations/llms/llama-index-llms-vertex/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-vertex/README.md",
"repo_id": "llama_index",
"token_count": 11
} | 1,304 |
{
"name": "test-exports-cf",
"version": "0.0.0",
"workspaces": [
"libs/*"
],
"devDependencies": {
"@cloudflare/workers-types": "^4.20230321.0"
},
"dependencies": {
"@langchain/anthropic": "workspace:*",
"@langchain/community": "workspace:*",
"@langchain/core": "workspace:*",
"@lang... | langchainjs/environment_tests/test-exports-cf/package.json/0 | {
"file_path": "langchainjs/environment_tests/test-exports-cf/package.json",
"repo_id": "langchainjs",
"token_count": 328
} | 830 |
# 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/decision_transformer/test_modeling_decision_transformer.py/0 | {
"file_path": "transformers/tests/models/decision_transformer/test_modeling_decision_transformer.py",
"repo_id": "transformers",
"token_count": 4241
} | 812 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/pt/pipeline_tutorial.md/0 | {
"file_path": "transformers/docs/source/pt/pipeline_tutorial.md",
"repo_id": "transformers",
"token_count": 2374
} | 503 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-txtai/llama_index/readers/txtai/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-txtai/llama_index/readers/txtai/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,563 |
"""Test Bookend AI embeddings."""
from langchain_community.embeddings.bookend import BookendEmbeddings
def test_bookend_embedding_documents() -> None:
"""Test Bookend AI embeddings for documents."""
documents = ["foo bar", "bar foo"]
embedding = BookendEmbeddings(
domain="<bookend_domain>",
... | langchain/libs/community/tests/integration_tests/embeddings/test_bookend.py/0 | {
"file_path": "langchain/libs/community/tests/integration_tests/embeddings/test_bookend.py",
"repo_id": "langchain",
"token_count": 348
} | 360 |
from ._registry import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", DeprecationWarning)
| pytorch-image-models/timm/models/registry.py/0 | {
"file_path": "pytorch-image-models/timm/models/registry.py",
"repo_id": "pytorch-image-models",
"token_count": 43
} | 388 |
"""Module for parsing text files.."""
from typing import Iterator
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseBlobParser
from langchain_community.document_loaders.blob_loaders import Blob
class TextParser(BaseBlobParser):
"""Parser for text blobs."""
... | langchain/libs/community/langchain_community/document_loaders/parsers/txt.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/txt.py",
"repo_id": "langchain",
"token_count": 159
} | 265 |
package indexparamcheck
import (
"fmt"
"strconv"
)
// ivfPQChecker checks if a IVF_PQ index can be built.
type ivfPQChecker struct {
ivfBaseChecker
}
// CheckTrain checks if ivf-pq index can be built with the specific index parameters.
func (c *ivfPQChecker) CheckTrain(params map[string]string) error {
if err :=... | milvus/pkg/util/indexparamcheck/ivf_pq_checker.go/0 | {
"file_path": "milvus/pkg/util/indexparamcheck/ivf_pq_checker.go",
"repo_id": "milvus",
"token_count": 584
} | 1,831 |
import { OpenAI } from "@langchain/openai";
import {
StructuredOutputParser,
RegexParser,
CombiningOutputParser,
} from "langchain/output_parsers";
import { PromptTemplate } from "@langchain/core/prompts";
const answerParser = StructuredOutputParser.fromNamesAndDescriptions({
answer: "answer to the user's ques... | langchainjs/examples/src/prompts/combining_parser.ts/0 | {
"file_path": "langchainjs/examples/src/prompts/combining_parser.ts",
"repo_id": "langchainjs",
"token_count": 773
} | 877 |
"""Pinecone reader."""
from typing import Any, Dict, List, Optional
from llama_index.legacy.readers.base import BaseReader
from llama_index.legacy.schema import Document
class PineconeReader(BaseReader):
"""Pinecone reader.
Args:
api_key (str): Pinecone API key.
environment (str): Pinecone ... | llama_index/llama-index-legacy/llama_index/legacy/readers/pinecone.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/readers/pinecone.py",
"repo_id": "llama_index",
"token_count": 788
} | 1,533 |
import candle
import torch
# convert from candle tensor to torch tensor
t = candle.randn((3, 512, 512))
torch_tensor = t.to_torch()
print(torch_tensor)
print(type(torch_tensor))
# convert from torch tensor to candle tensor
t = torch.randn((3, 512, 512))
candle_tensor = candle.Tensor(t)
print(candle_tensor)
print(type... | candle/candle-pyo3/test_pytorch.py/0 | {
"file_path": "candle/candle-pyo3/test_pytorch.py",
"repo_id": "candle",
"token_count": 126
} | 75 |
{
"openapi": "3.1.0",
"info": {
"title": "WolframAlpha",
"version": "v1.7"
},
"servers": [
{
"url": "https://www.wolframalpha.com",
"description": "The WolframAlpha server"
}
],
"paths": {
"/api/v1/spoken.jsp": {
"get": {
"operationI... | langchain/libs/langchain/tests/unit_tests/examples/test_specs/wolframcloud/apispec.json/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/examples/test_specs/wolframcloud/apispec.json",
"repo_id": "langchain",
"token_count": 4747
} | 640 |
# 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... | trl/trl/trainer/reward_trainer.py/0 | {
"file_path": "trl/trl/trainer/reward_trainer.py",
"repo_id": "trl",
"token_count": 5943
} | 782 |
<jupyter_start><jupyter_text>Hugging Face LLMsThere are many ways to interface with LLMs from [Hugging Face](https://huggingface.co/).Hugging Face itself provides several Python packages to enable access,which LlamaIndex wraps into `LLM` entities:- The [`transformers`](https://github.com/huggingface/transformers) packa... | llama_index/docs/examples/llm/huggingface.ipynb/0 | {
"file_path": "llama_index/docs/examples/llm/huggingface.ipynb",
"repo_id": "llama_index",
"token_count": 1154
} | 1,143 |
"""Azure OpenAI embeddings wrapper."""
from __future__ import annotations
import os
import warnings
from typing import Callable, Dict, Optional, Union
from langchain_core._api.deprecation import deprecated
from langchain_core.pydantic_v1 import Field, root_validator
from langchain_core.utils import get_from_dict_or_e... | langchain/libs/community/langchain_community/embeddings/azure_openai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/embeddings/azure_openai.py",
"repo_id": "langchain",
"token_count": 3483
} | 255 |
# coding=utf-8
# Copyright 2019-present, Facebook, Inc and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | transformers/src/transformers/models/xlm/modeling_xlm.py/0 | {
"file_path": "transformers/src/transformers/models/xlm/modeling_xlm.py",
"repo_id": "transformers",
"token_count": 24030
} | 772 |
import pytest
@pytest.fixture(scope="module")
def mt0_base_handle(launcher):
with launcher("bigscience/mt0-base") as handle:
yield handle
@pytest.fixture(scope="module")
async def mt0_base(mt0_base_handle):
await mt0_base_handle.health(300)
return mt0_base_handle.client
@pytest.mark.asyncio
as... | text-generation-inference/integration-tests/models/test_mt0_base.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_mt0_base.py",
"repo_id": "text-generation-inference",
"token_count": 713
} | 428 |
[tool.poetry]
name = "sql-llamacpp"
version = "0.1.0"
description = "Private QA with a SQL database using natural language and a local LLM via llama.cpp"
authors = [
"Lance Martin <lance@langchain.dev>",
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = "^0.1"
llama-cpp-python =... | langchain/templates/sql-llamacpp/pyproject.toml/0 | {
"file_path": "langchain/templates/sql-llamacpp/pyproject.toml",
"repo_id": "langchain",
"token_count": 280
} | 708 |
# coding=utf-8
# Copyright 2020-present 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 ap... | transformers/src/transformers/trainer_utils.py/0 | {
"file_path": "transformers/src/transformers/trainer_utils.py",
"repo_id": "transformers",
"token_count": 11573
} | 688 |
import { expect, test } from "@jest/globals";
import { OpenAIEmbeddings } from "@langchain/openai";
import { VercelPostgres } from "../vercel_postgres.js";
let vercelPostgresStore: VercelPostgres;
const config = {
tableName: "testvercelvectorstorelangchain2",
columns: {
idColumnName: "id",
vectorColumnNam... | langchainjs/libs/langchain-community/src/vectorstores/tests/vercel_postgres.int.test.ts/0 | {
"file_path": "langchainjs/libs/langchain-community/src/vectorstores/tests/vercel_postgres.int.test.ts",
"repo_id": "langchainjs",
"token_count": 1233
} | 975 |
<jupyter_start><jupyter_text>Tokenisation *Byte-Pair Encoding* Installez les bibliothèques 🤗 *Transformers* et 🤗 *Datasets* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
corpus = [
"C'est le cours d'Hugging Face.",
"Ce chapitre traite de la tokenisation.",
"Ce... | notebooks/course/fr/chapter6/section5.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter6/section5.ipynb",
"repo_id": "notebooks",
"token_count": 1572
} | 301 |
/******************************************************************************
* Copyright (c) 2023, Tri Dao.
******************************************************************************/
#pragma once
#include <cuda.h>
#include <vector>
constexpr int TOTAL_DIM = 0;
constexpr int H_DIM = 1;
constexpr int D_DIM =... | candle/candle-flash-attn/kernels/flash.h/0 | {
"file_path": "candle/candle-flash-attn/kernels/flash.h",
"repo_id": "candle",
"token_count": 2033
} | 56 |
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