text stringlengths 3 1.68M | id stringlengths 13 169 | metadata dict | __index_level_0__ int64 0 2.21k |
|---|---|---|---|
# 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/src/transformers/models/vit/image_processing_vit.py/0 | {
"file_path": "transformers/src/transformers/models/vit/image_processing_vit.py",
"repo_id": "transformers",
"token_count": 5684
} | 709 |
import fnmatch
import json
import os
import shutil
import tempfile
import xml.etree.ElementTree as ET
from argparse import ArgumentParser
from pathlib import Path
from typing import Optional
from datasets import config
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import D... | datasets/src/datasets/commands/dummy_data.py/0 | {
"file_path": "datasets/src/datasets/commands/dummy_data.py",
"repo_id": "datasets",
"token_count": 11107
} | 137 |
"""Chain that interprets a prompt and executes python code to do math.
Heavily borrowed from llm_math, wrapper for SymPy
"""
| langchain/libs/experimental/langchain_experimental/llm_symbolic_math/__init__.py/0 | {
"file_path": "langchain/libs/experimental/langchain_experimental/llm_symbolic_math/__init__.py",
"repo_id": "langchain",
"token_count": 34
} | 462 |
<div align="center">
<h1><code>create-wasm-app</code></h1>
<strong>An <code>npm init</code> template for kick starting a project that uses NPM packages containing Rust-generated WebAssembly and bundles them with Webpack.</strong>
<p>
<a href="https://travis-ci.org/rustwasm/create-wasm-app"><img src="https:... | tokenizers/tokenizers/examples/unstable_wasm/www/README.md/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/README.md",
"repo_id": "tokenizers",
"token_count": 893
} | 473 |
<jupyter_start><jupyter_code>from utils import get_train_str, get_train_and_eval_data, get_eval_preds, train_prompt
import warnings
warnings.filterwarnings("ignore")
warnings.simplefilter("ignore")
# load up the titanic data
train_df, train_labels, eval_df, eval_labels = get_train_and_eval_data("data/train.csv")<jupy... | llama_index/experimental/classifier/TitanicModel.ipynb/0 | {
"file_path": "llama_index/experimental/classifier/TitanicModel.ipynb",
"repo_id": "llama_index",
"token_count": 1769
} | 1,155 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/src/diffusers/models/unets/unet_motion_model.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/unet_motion_model.py",
"repo_id": "diffusers",
"token_count": 18715
} | 228 |
python_sources()
python_tests(
name="tests",
)
| llama_index/llama-index-core/tests/output_parsers/BUILD/0 | {
"file_path": "llama_index/llama-index-core/tests/output_parsers/BUILD",
"repo_id": "llama_index",
"token_count": 22
} | 1,239 |
[
{
"server": "idc-sh005",
"suite_params": [
{
"suite": "2_locust_insert.yaml",
"image_type": "cpu"
}
]
}
]
| milvus/tests/benchmark/milvus_benchmark/scheduler/locust_insert.json/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/scheduler/locust_insert.json",
"repo_id": "milvus",
"token_count": 137
} | 1,940 |
import {
ChatOpenAI,
type ChatOpenAICallOptions,
messageToOpenAIRole,
} from "@langchain/openai";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { BaseMessage, ChatMessage } from "@langchain/core/messages";
import { ChatResult } from "@langchain/core/outputs";
import { promp... | langchainjs/langchain/src/chat_models/openai.ts/0 | {
"file_path": "langchainjs/langchain/src/chat_models/openai.ts",
"repo_id": "langchainjs",
"token_count": 1993
} | 889 |
# Building Milvus with Docker
Building Milvus is easy if you take advantage of the containerized build environment. This document will guide you through this build process.
1. Docker, using one of the following configurations:
- **macOS** Install Docker for Mac. See installation instructions [here](https://docs.dock... | milvus/build/README.md/0 | {
"file_path": "milvus/build/README.md",
"repo_id": "milvus",
"token_count": 2720
} | 1,711 |
from typing import Any, List
def stringify_value(val: Any) -> str:
"""Stringify a value.
Args:
val: The value to stringify.
Returns:
str: The stringified value.
"""
if isinstance(val, str):
return val
elif isinstance(val, dict):
return "\n" + stringify_dict(va... | langchain/libs/core/langchain_core/utils/strings.py/0 | {
"file_path": "langchain/libs/core/langchain_core/utils/strings.py",
"repo_id": "langchain",
"token_count": 373
} | 441 |
# Models
For more detail on the models, please refer to the [docs](https://huggingface.co/docs/diffusers/api/models/overview). | diffusers/src/diffusers/models/README.md/0 | {
"file_path": "diffusers/src/diffusers/models/README.md",
"repo_id": "diffusers",
"token_count": 39
} | 222 |
""" This file is for LLMRails Embedding """
from typing import Dict, List, Optional
import requests
from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
class LL... | langchain/libs/community/langchain_community/embeddings/llm_rails.py/0 | {
"file_path": "langchain/libs/community/langchain_community/embeddings/llm_rails.py",
"repo_id": "langchain",
"token_count": 975
} | 253 |
# Copyright 2022 The HuggingFace Team and Brian Chao. 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 requir... | accelerate/src/accelerate/commands/menu/cursor.py/0 | {
"file_path": "accelerate/src/accelerate/commands/menu/cursor.py",
"repo_id": "accelerate",
"token_count": 763
} | 12 |
import { ChatPromptTemplate } from "@langchain/core/prompts";
const prompt = ChatPromptTemplate.fromMessages([
["human", "Tell me a short joke about {topic}"],
]);
const promptValue = await prompt.invoke({ topic: "ice cream" });
console.log(promptValue);
/**
ChatPromptValue {
messages: [
HumanMessage {
c... | langchainjs/examples/src/guides/expression_language/get_started/prompt.ts/0 | {
"file_path": "langchainjs/examples/src/guides/expression_language/get_started/prompt.ts",
"repo_id": "langchainjs",
"token_count": 262
} | 808 |
{
"openapi": "3.0.1",
"info": {
"title": "News Plugin",
"description": "A plugin that allows the user to obtain and summary latest news using ChatGPT. If you do not know the user's username, ask them first before making queries to the plugin. Otherwise, use the username \"global\".",
"version": ... | langchain/libs/community/tests/unit_tests/examples/test_specs/freetv-app/apispec.json/0 | {
"file_path": "langchain/libs/community/tests/unit_tests/examples/test_specs/freetv-app/apispec.json",
"repo_id": "langchain",
"token_count": 1866
} | 405 |
// 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/accesslog/minio_handler.go/0 | {
"file_path": "milvus/internal/proxy/accesslog/minio_handler.go",
"repo_id": "milvus",
"token_count": 2912
} | 1,739 |
# coding=utf-8
# Copyright 2019-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 a... | transformers/examples/research_projects/distillation/scripts/binarized_data.py/0 | {
"file_path": "transformers/examples/research_projects/distillation/scripts/binarized_data.py",
"repo_id": "transformers",
"token_count": 1428
} | 584 |
package model
type CollectionMetadataValueType interface {
IsCollectionMetadataValueType()
Equals(other CollectionMetadataValueType) bool
}
type CollectionMetadataValueStringType struct {
Value string
}
func (s *CollectionMetadataValueStringType) IsCollectionMetadataValueType() {}
func (s *CollectionMetadataValu... | chroma/go/coordinator/internal/model/collection_metadata.go/0 | {
"file_path": "chroma/go/coordinator/internal/model/collection_metadata.go",
"repo_id": "chroma",
"token_count": 730
} | 51 |
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: HuggingFace's Tokenizers
message: >-
Fast State-of-the-Art Tokenizers optimized for Research
and Production.
type: software
authors:
- given-names: Anthony
family-names: Moi
... | tokenizers/CITATION.cff/0 | {
"file_path": "tokenizers/CITATION.cff",
"repo_id": "tokenizers",
"token_count": 293
} | 448 |
# 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... | diffusers/src/diffusers/utils/constants.py/0 | {
"file_path": "diffusers/src/diffusers/utils/constants.py",
"repo_id": "diffusers",
"token_count": 819
} | 260 |
// 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/cmd/components/index_node.go/0 | {
"file_path": "milvus/cmd/components/index_node.go",
"repo_id": "milvus",
"token_count": 752
} | 1,614 |
import logging
import time
from typing import Dict, Iterator, Optional, Tuple
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseBlobParser
from langchain_community.document_loaders.blob_loaders import Blob
from langchain_community.utils.openai import is_openai_v1
... | langchain/libs/community/langchain_community/document_loaders/parsers/audio.py/0 | {
"file_path": "langchain/libs/community/langchain_community/document_loaders/parsers/audio.py",
"repo_id": "langchain",
"token_count": 5027
} | 253 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/internal/core/src/segcore/SegcoreConfig.cpp/0 | {
"file_path": "milvus/internal/core/src/segcore/SegcoreConfig.cpp",
"repo_id": "milvus",
"token_count": 1731
} | 1,799 |
"""Init file."""
| llama_index/llama-index-core/llama_index/core/indices/common/__init__.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/indices/common/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,175 |
use crate::backend::BackendDevice;
use crate::cpu_backend::CpuDevice;
use crate::{CpuStorage, DType, Result, Shape, Storage, WithDType};
/// A `DeviceLocation` represents a physical device whereas multiple `Device`
/// can live on the same location (typically for cuda devices).
#[derive(Debug, Copy, Clone, PartialEq, ... | candle/candle-core/src/device.rs/0 | {
"file_path": "candle/candle-core/src/device.rs",
"repo_id": "candle",
"token_count": 5149
} | 35 |
<jupyter_start><jupyter_text>Microsoft PowerPoint>[Microsoft PowerPoint](https://en.wikipedia.org/wiki/Microsoft_PowerPoint) is a presentation program by Microsoft.This covers how to load `Microsoft PowerPoint` documents into a document format that we can use downstream.<jupyter_code>from langchain_community.document_l... | langchain/docs/docs/integrations/document_loaders/microsoft_powerpoint.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/microsoft_powerpoint.ipynb",
"repo_id": "langchain",
"token_count": 251
} | 106 |
<jupyter_start><jupyter_text>Tencent COS Directory>[Tencent Cloud Object Storage (COS)](https://www.tencentcloud.com/products/cos) is a distributed > storage service that enables you to store any amount of data from anywhere via HTTP/HTTPS protocols. > `COS` has no restrictions on data structure or format. It also has ... | langchain/docs/docs/integrations/document_loaders/tencent_cos_directory.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/document_loaders/tencent_cos_directory.ipynb",
"repo_id": "langchain",
"token_count": 398
} | 107 |
<!--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/optimization/deepcache.md/0 | {
"file_path": "diffusers/docs/source/en/optimization/deepcache.md",
"repo_id": "diffusers",
"token_count": 1912
} | 179 |
<jupyter_start><jupyter_code>import openai
openai.api_key = "sk-your-key"
from llama_index.agent import OpenAIAgent
# Load the Plugin
import requests
import yaml
f = requests.get(
"https://raw.githubusercontent.com/sisbell/chatgpt-plugin-store/main/manifests/today-currency-converter.oiconma.repl.co.json"
).text
m... | llama_index/llama-index-integrations/tools/llama-index-tools-chatgpt-plugin/examples/chatgpt_plugin.ipynb/0 | {
"file_path": "llama_index/llama-index-integrations/tools/llama-index-tools-chatgpt-plugin/examples/chatgpt_plugin.ipynb",
"repo_id": "llama_index",
"token_count": 699
} | 1,473 |
"""Init params."""
| llama_index/llama-index-legacy/tests/indices/query/__init__.py/0 | {
"file_path": "llama_index/llama-index-legacy/tests/indices/query/__init__.py",
"repo_id": "llama_index",
"token_count": 6
} | 1,632 |
// 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/storage/PayloadWriter.h/0 | {
"file_path": "milvus/internal/core/src/storage/PayloadWriter.h",
"repo_id": "milvus",
"token_count": 598
} | 1,758 |
[tool.poetry]
name = "rag-chroma-multi-modal"
version = "0.1.0"
description = "Multi-modal RAG using Chroma"
authors = [
"Lance Martin <lance@langchain.dev>",
]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain = ">=0.0.353,<0.2"
openai = "<2"
tiktoken = ">=0.5.1"
chromadb = ">=0.4.... | langchain/templates/rag-chroma-multi-modal/pyproject.toml/0 | {
"file_path": "langchain/templates/rag-chroma-multi-modal/pyproject.toml",
"repo_id": "langchain",
"token_count": 371
} | 713 |
from typing import Any, Callable, Optional, Sequence
from llama_index.core.base.embeddings.base import (
BaseEmbedding,
SimilarityMode,
similarity,
)
from llama_index.core.evaluation.base import BaseEvaluator, EvaluationResult
from llama_index.core.prompts.mixin import PromptDictType
from llama_index.core.... | llama_index/llama-index-core/llama_index/core/evaluation/semantic_similarity.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/evaluation/semantic_similarity.py",
"repo_id": "llama_index",
"token_count": 1201
} | 1,257 |
"""Anyscale Endpoints chat wrapper. Relies heavily on ChatOpenAI."""
from __future__ import annotations
import logging
import os
import sys
from typing import TYPE_CHECKING, Dict, Optional, Set
import requests
from langchain_core.messages import BaseMessage
from langchain_core.pydantic_v1 import Field, SecretStr, roo... | langchain/libs/community/langchain_community/chat_models/anyscale.py/0 | {
"file_path": "langchain/libs/community/langchain_community/chat_models/anyscale.py",
"repo_id": "langchain",
"token_count": 3619
} | 236 |
.. _Ref-Memory
Memory
======
.. automodule:: llama_index.core.memory
:members:
:inherited-members:
| llama_index/docs/api_reference/memory.rst/0 | {
"file_path": "llama_index/docs/api_reference/memory.rst",
"repo_id": "llama_index",
"token_count": 42
} | 1,036 |
use std::error::Error;
use vergen::EmitBuilder;
fn main() -> Result<(), Box<dyn Error>> {
// Emit cargo and rustc compile time values
EmitBuilder::builder().all_cargo().all_rustc().emit()?;
// Try to get the git sha from the local git repository
if EmitBuilder::builder()
.fail_on_error()
... | text-generation-inference/launcher/build.rs/0 | {
"file_path": "text-generation-inference/launcher/build.rs",
"repo_id": "text-generation-inference",
"token_count": 363
} | 414 |
"""Test formatting functionality."""
from typing import Union
import pytest
from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
from langchain_core.documents import Document
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
ChatMessage,
ChatMessageChunk,
... | langchain/libs/langchain/tests/unit_tests/test_schema.py/0 | {
"file_path": "langchain/libs/langchain/tests/unit_tests/test_schema.py",
"repo_id": "langchain",
"token_count": 1447
} | 636 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-stripe/llama_index/readers/airbyte_stripe/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airbyte-stripe/llama_index/readers/airbyte_stripe/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,313 |
from typing import Any, Dict, List
import requests
from langchain_core.embeddings import Embeddings
from langchain_core.pydantic_v1 import BaseModel, Extra
DEFAULT_MODEL_NAME = "@cf/baai/bge-base-en-v1.5"
class CloudflareWorkersAIEmbeddings(BaseModel, Embeddings):
"""Cloudflare Workers AI embedding model.
... | langchain/libs/community/langchain_community/embeddings/cloudflare_workersai.py/0 | {
"file_path": "langchain/libs/community/langchain_community/embeddings/cloudflare_workersai.py",
"repo_id": "langchain",
"token_count": 1327
} | 268 |
import json
import logging
from pathlib import Path
from typing import Iterator, Union
from langchain_core.chat_sessions import ChatSession
from langchain_core.messages import HumanMessage
from langchain_community.chat_loaders.base import BaseChatLoader
logger = logging.getLogger(__file__)
class SingleFileFacebook... | langchain/libs/community/langchain_community/chat_loaders/facebook_messenger.py/0 | {
"file_path": "langchain/libs/community/langchain_community/chat_loaders/facebook_messenger.py",
"repo_id": "langchain",
"token_count": 1165
} | 232 |
# Extraction
Most APIs and databases still deal with structured information. Therefore, in order to better work with those, it can be useful to extract structured information from text. Examples of this include:
- Extracting a structured row to insert into a database from a sentence
- Extracting multiple rows to inse... | langchainjs/docs/core_docs/docs/use_cases/extraction.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/use_cases/extraction.mdx",
"repo_id": "langchainjs",
"token_count": 505
} | 775 |
python_sources()
| llama_index/llama-index-core/tests/mock_utils/BUILD/0 | {
"file_path": "llama_index/llama-index-core/tests/mock_utils/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,154 |
<jupyter_start><jupyter_text>BM25 RetrieverIn this guide, we define a bm25 retriever that search documents using bm25 method.This notebook is very similar to the RouterQueryEngine notebook. Setup If you're opening this Notebook on colab, you will probably need to install LlamaIndex ๐ฆ.<jupyter_code>%pip install llama-... | llama_index/docs/examples/retrievers/bm25_retriever.ipynb/0 | {
"file_path": "llama_index/docs/examples/retrievers/bm25_retriever.ipynb",
"repo_id": "llama_index",
"token_count": 2943
} | 1,106 |
from llama_index.vector_stores.epsilla.base import EpsillaVectorStore
__all__ = ["EpsillaVectorStore"]
| llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-epsilla/llama_index/vector_stores/epsilla/__init__.py/0 | {
"file_path": "llama_index/llama-index-integrations/vector_stores/llama-index-vector-stores-epsilla/llama_index/vector_stores/epsilla/__init__.py",
"repo_id": "llama_index",
"token_count": 33
} | 1,463 |
# coding=utf-8
# Copyright 2022 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 law... | transformers/tests/models/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py/0 | {
"file_path": "transformers/tests/models/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py",
"repo_id": "transformers",
"token_count": 17887
} | 771 |
<jupyter_start><jupyter_text>AnalyticDB>[AnalyticDB for PostgreSQL](https://www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview) is a massively parallel processing (MPP) data warehousing service that is designed to analyze large volumes of data online.>`AnalyticDB for PostgreSQL`... | langchain/docs/docs/integrations/vectorstores/analyticdb.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/vectorstores/analyticdb.ipynb",
"repo_id": "langchain",
"token_count": 1073
} | 185 |
# 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/src/transformers/models/segformer/image_processing_segformer.py/0 | {
"file_path": "transformers/src/transformers/models/segformer/image_processing_segformer.py",
"repo_id": "transformers",
"token_count": 9996
} | 677 |
export PYTHONPATH="../":"${PYTHONPATH}"
python use_own_knowledge_dataset.py
ray start --head
python finetune_rag.py \
--model_name_or_path facebook/rag-token-base \
--model_type rag_token \
--context_encoder_name facebook/dpr-ctx_encoder-multiset-base \
--fp16 \
--gpus 1 \
--profile \
--e... | transformers/examples/research_projects/rag-end2end-retriever/test_run/test_rag_new_features.sh/0 | {
"file_path": "transformers/examples/research_projects/rag-end2end-retriever/test_run/test_rag_new_features.sh",
"repo_id": "transformers",
"token_count": 153
} | 541 |
# Model arguments
model_name_or_path: mistralai/Mistral-7B-v0.1
model_revision: main
torch_dtype: float16
# LoRA arguments
load_in_4bit: true
use_peft: true
lora_r: 16
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
- gate_proj
- up_proj
- down_proj
# Data training arguments... | alignment-handbook/recipes/zephyr-7b-beta/sft/config_qlora.yaml/0 | {
"file_path": "alignment-handbook/recipes/zephyr-7b-beta/sft/config_qlora.yaml",
"repo_id": "alignment-handbook",
"token_count": 646
} | 22 |
<!--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/layoutlm.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/layoutlm.md",
"repo_id": "transformers",
"token_count": 2088
} | 508 |
from langchain_community.document_loaders.facebook_chat import (
FacebookChatLoader,
concatenate_rows,
)
__all__ = ["concatenate_rows", "FacebookChatLoader"]
| langchain/libs/langchain/langchain/document_loaders/facebook_chat.py/0 | {
"file_path": "langchain/libs/langchain/langchain/document_loaders/facebook_chat.py",
"repo_id": "langchain",
"token_count": 56
} | 527 |
from langchain.chains.query_constructor.schema import AttributeInfo
from langchain.schema import Document
# Qdrant collection name
DEFAULT_COLLECTION_NAME = "restaurants"
# Here is a description of the dataset and metadata attributes. Metadata attributes will
# be used to filter the results of the query beyond the se... | langchain/templates/self-query-qdrant/self_query_qdrant/defaults.py/0 | {
"file_path": "langchain/templates/self-query-qdrant/self_query_qdrant/defaults.py",
"repo_id": "langchain",
"token_count": 1893
} | 732 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/pix2struct/test_modeling_pix2struct.py/0 | {
"file_path": "transformers/tests/models/pix2struct/test_modeling_pix2struct.py",
"repo_id": "transformers",
"token_count": 15362
} | 818 |
<!--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/ja/tutorials/autopipeline.md/0 | {
"file_path": "diffusers/docs/source/ja/tutorials/autopipeline.md",
"repo_id": "diffusers",
"token_count": 4100
} | 194 |
import ignore, { Ignore } from "ignore";
import binaryExtensions from "binary-extensions";
import { Document } from "@langchain/core/documents";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import {
AsyncCaller,
AsyncCallerParams,
} from "@langchain/core/utils/async_caller";
import { BaseDoc... | langchainjs/langchain/src/document_loaders/web/github.ts/0 | {
"file_path": "langchainjs/langchain/src/document_loaders/web/github.ts",
"repo_id": "langchainjs",
"token_count": 8009
} | 976 |
{
"modelname": "TemplatePT",
"uppercase_modelname": "TEMPLATE_PT",
"lowercase_modelname": "template_pt",
"camelcase_modelname": "TemplatePt",
"authors": "The HuggingFace Team",
"checkpoint_identifier": "brand-new-bert-base-cased",
"tokenizer_type": "Based on BERT",
"generate_tensorflow_pytorch_and_flax"... | transformers/templates/adding_a_new_model/tests/pt-encoder-bert-tokenizer.json/0 | {
"file_path": "transformers/templates/adding_a_new_model/tests/pt-encoder-bert-tokenizer.json",
"repo_id": "transformers",
"token_count": 148
} | 713 |
// 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/datacoord/broker/coordinator_broker_test.go/0 | {
"file_path": "milvus/internal/datacoord/broker/coordinator_broker_test.go",
"repo_id": "milvus",
"token_count": 3328
} | 1,688 |
import {
similarity as ml_distance_similarity,
distance as ml_distance,
} from "ml-distance";
type VectorFunction = (xVector: number[], yVector: number[]) => number;
/**
* Apply a row-wise function between two matrices with the same number of columns.
*
* @param {number[][]} X - The first matrix.
* @param {nu... | langchainjs/langchain-core/src/utils/math.ts/0 | {
"file_path": "langchainjs/langchain-core/src/utils/math.ts",
"repo_id": "langchainjs",
"token_count": 1816
} | 875 |
"""Utilities to use Google provided components."""
from importlib import metadata
from typing import Any, Optional
def get_client_info(module: Optional[str] = None) -> Any:
r"""Returns a custom user agent header.
Args:
module (Optional[str]):
Optional. The module for a custom user agent ... | langchain/libs/community/langchain_community/utils/google.py/0 | {
"file_path": "langchain/libs/community/langchain_community/utils/google.py",
"repo_id": "langchain",
"token_count": 281
} | 306 |
# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class Pop2PianoFeatureExtractor(metaclass=DummyObject):
_backends = ["essentia", "librosa", "pretty_midi", "scipy", "torch"]
def __init__(self, *args, **kwargs):
requires_bac... | transformers/src/transformers/utils/dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objects.py/0 | {
"file_path": "transformers/src/transformers/utils/dummy_essentia_and_librosa_and_pretty_midi_and_scipy_and_torch_objects.py",
"repo_id": "transformers",
"token_count": 367
} | 770 |
import { Html, Head, Main, NextScript } from 'next/document'
export default function Document() {
return (
<Html lang="en">
<Head />
<body>
<Main />
<NextScript />
</body>
</Html>
)
}
| langchainjs/environment_tests/test-exports-vercel/src/pages/_document.tsx/0 | {
"file_path": "langchainjs/environment_tests/test-exports-vercel/src/pages/_document.tsx",
"repo_id": "langchainjs",
"token_count": 105
} | 785 |
from langchain_community.embeddings.llm_rails import LLMRailsEmbeddings
__all__ = ["LLMRailsEmbeddings"]
| langchain/libs/langchain/langchain/embeddings/llm_rails.py/0 | {
"file_path": "langchain/libs/langchain/langchain/embeddings/llm_rails.py",
"repo_id": "langchain",
"token_count": 37
} | 508 |
python_sources()
| llama_index/llama-index-packs/llama-index-packs-chroma-autoretrieval/llama_index/packs/chroma_autoretrieval/BUILD/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-chroma-autoretrieval/llama_index/packs/chroma_autoretrieval/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,558 |
---
sidebar_position: 5
sidebar_class_name: hidden
---
# Callbacks
LangChain provides a callbacks system that allows you to hook into the various stages of your LLM application. This is useful for logging, monitoring, streaming, and other tasks.
import CodeBlock from "@theme/CodeBlock";
You can subscribe to these e... | langchainjs/docs/core_docs/docs/modules/callbacks/index.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/callbacks/index.mdx",
"repo_id": "langchainjs",
"token_count": 1340
} | 751 |
import threading
import h5py
import numpy as np
import time
import sys
import copy
from pathlib import Path
from loguru import logger
import pymilvus
from pymilvus import (
connections,
FieldSchema, CollectionSchema, DataType,
Collection, utility
)
pymilvus_version = pymilvus.__version__
all_index_types ... | milvus/tests/python_client/deploy/scripts/first_recall_test.py/0 | {
"file_path": "milvus/tests/python_client/deploy/scripts/first_recall_test.py",
"repo_id": "milvus",
"token_count": 3120
} | 1,976 |
/// <reference types="next" />
/// <reference types="next/image-types/global" />
// NOTE: This file should not be edited
// see https://nextjs.org/docs/basic-features/typescript for more information.
| auto-evaluator/nextjs/next-env.d.ts/0 | {
"file_path": "auto-evaluator/nextjs/next-env.d.ts",
"repo_id": "auto-evaluator",
"token_count": 58
} | 3 |
<jupyter_start><jupyter_text>Huggingface Sagemaker-sdk - Distributed Training Demo for `TensorFlow` Distributed Data Parallelism with `transformers` and `tensorflow` 1. [Introduction](Introduction) 2. [Development Environment and Permissions](Development-Environment-and-Permissions) 1. [Installation](Installation) ... | notebooks/sagemaker/07_tensorflow_distributed_training_data_parallelism/sagemaker-notebook.ipynb/0 | {
"file_path": "notebooks/sagemaker/07_tensorflow_distributed_training_data_parallelism/sagemaker-notebook.ipynb",
"repo_id": "notebooks",
"token_count": 3614
} | 312 |
<jupyter_start><jupyter_text>LocalAI[LocalAI](https://github.com/mudler/LocalAI) is a method of serving modelsthrough an OpenAI API spec-compatible REST API.LlamaIndex can use its `OpenAILike` LLM to directly interact with a LocalAI server. Setting Up LocalAIFirst, let's get LocalAI set up locally.```bashgit clone git@... | llama_index/docs/examples/llm/localai.ipynb/0 | {
"file_path": "llama_index/docs/examples/llm/localai.ipynb",
"repo_id": "llama_index",
"token_count": 1501
} | 1,127 |
// 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/mock_test.go/0 | {
"file_path": "milvus/internal/proxy/mock_test.go",
"repo_id": "milvus",
"token_count": 7324
} | 1,829 |
---
sidebar_class_name: hidden
---
import CodeBlock from "@theme/CodeBlock";
import CancellationExample from "@examples/agents/agent_cancellation.ts";
# Cancelling requests
You can cancel a request by passing a `signal` option when you run the agent. For example:
import IntegrationInstallTooltip from "@mdx_componen... | langchainjs/docs/core_docs/docs/modules/agents/how_to/cancelling_requests.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/modules/agents/how_to/cancelling_requests.mdx",
"repo_id": "langchainjs",
"token_count": 201
} | 749 |
search_performance:
collections:
# -
# server:
# db_config.primary_path: /test/milvus/db_data_8/sift_1b_2048_128_l2_sq8
# cache_config.cpu_cache_capacity: 150
# engine_config.use_blas_threshold: 0
# engine_config.gpu_search_threshold: 200
# gpu_resource_config.enable: true
#... | milvus/tests/benchmark/milvus_benchmark/suites/search_debug.yaml/0 | {
"file_path": "milvus/tests/benchmark/milvus_benchmark/suites/search_debug.yaml",
"repo_id": "milvus",
"token_count": 1489
} | 1,884 |
# Create a dataset loading script
<Tip>
The dataset loading script is likely not needed if your dataset is in one of the following formats: CSV, JSON, JSON lines, text, images, audio or Parquet.
With those formats, you should be able to load your dataset automatically with [`~datasets.load_dataset`],
as long as your... | datasets/docs/source/dataset_script.mdx/0 | {
"file_path": "datasets/docs/source/dataset_script.mdx",
"repo_id": "datasets",
"token_count": 5380
} | 120 |
---
sidebar_label: Google PaLM
---
import CodeBlock from "@theme/CodeBlock";
# Google PaLM
:::note
This integration does not support `embeddings-*` model. Check [Google AI](/docs/integrations/text_embedding/google_generativeai) embeddings.
:::
The [Google PaLM API](https://developers.generativeai.google/products/pa... | langchainjs/docs/core_docs/docs/integrations/text_embedding/google_palm.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/integrations/text_embedding/google_palm.mdx",
"repo_id": "langchainjs",
"token_count": 308
} | 712 |
<!--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/api/schedulers/lcm.md/0 | {
"file_path": "diffusers/docs/source/en/api/schedulers/lcm.md",
"repo_id": "diffusers",
"token_count": 291
} | 165 |
# Airtable Loader
This loader loads documents from Airtable. The user specifies an API token to initialize the AirtableReader. They then specify a `table_id` and a `base_id` to load in the corresponding Document objects.
## Usage
Here's an example usage of the AirtableReader.
```python
from llama_index import downl... | llama_index/llama-index-integrations/readers/llama-index-readers-airtable/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-airtable/README.md",
"repo_id": "llama_index",
"token_count": 264
} | 1,329 |
import copy
import json
import os
import time
import numpy as np
import pandas as pd
import random
from faker import Faker
from sklearn import preprocessing
from common.common_func import gen_unique_str
from common.minio_comm import copy_files_to_minio
from utils.util_log import test_log as log
data_source = "/tmp/bu... | milvus/tests/python_client/common/bulk_insert_data.py/0 | {
"file_path": "milvus/tests/python_client/common/bulk_insert_data.py",
"repo_id": "milvus",
"token_count": 23392
} | 1,998 |
python_sources()
| llama_index/llama-index-integrations/readers/llama-index-readers-jira/llama_index/readers/jira/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-jira/llama_index/readers/jira/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,394 |
# LlamaIndex Llms Integration: Xinference
| llama_index/llama-index-integrations/llms/llama-index-llms-xinference/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-xinference/README.md",
"repo_id": "llama_index",
"token_count": 11
} | 1,307 |
# docstyle-ignore
INSTALL_CONTENT = """
# Transformers ์ค์น ๋ฐฉ๋ฒ
! pip install transformers datasets
# ๋ง์ง๋ง ๋ฆด๋ฆฌ์ค ๋์ ์์ค์์ ์ค์นํ๋ ค๋ฉด, ์ ๋ช
๋ น์ ์ฃผ์์ผ๋ก ๋ฐ๊พธ๊ณ ์๋ ๋ช
๋ น์ ํด์ ํ์ธ์.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
notebook_first_cells = [{"type": "code", "content": INSTALL_CONTENT}]
black_avoid_patterns = {
... | transformers/docs/source/ko/_config.py/0 | {
"file_path": "transformers/docs/source/ko/_config.py",
"repo_id": "transformers",
"token_count": 257
} | 538 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. and Baidu team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | transformers/tests/models/ernie_m/test_modeling_ernie_m.py/0 | {
"file_path": "transformers/tests/models/ernie_m/test_modeling_ernie_m.py",
"repo_id": "transformers",
"token_count": 5555
} | 722 |
<!--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/ja/model_doc/deformable_detr.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/deformable_detr.md",
"repo_id": "transformers",
"token_count": 1792
} | 518 |
export const chunkArray = <T>(arr: T[], chunkSize: number) =>
arr.reduce((chunks, elem, index) => {
const chunkIndex = Math.floor(index / chunkSize);
const chunk = chunks[chunkIndex] || [];
// eslint-disable-next-line no-param-reassign
chunks[chunkIndex] = chunk.concat([elem]);
return chunks;
},... | langchainjs/langchain-core/src/utils/chunk_array.ts/0 | {
"file_path": "langchainjs/langchain-core/src/utils/chunk_array.ts",
"repo_id": "langchainjs",
"token_count": 125
} | 870 |
from llama_index.core.readers.base import BaseReader
from llama_index.readers.awadb import AwadbReader
def test_class():
names_of_base_classes = [b.__name__ for b in AwadbReader.__mro__]
assert BaseReader.__name__ in names_of_base_classes
| llama_index/llama-index-integrations/readers/llama-index-readers-awadb/tests/test_readers_awadb.py/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-awadb/tests/test_readers_awadb.py",
"repo_id": "llama_index",
"token_count": 91
} | 1,267 |
import { logVersion010MigrationWarning } from "../util/entrypoint_deprecation.js";
/* #__PURE__ */ logVersion010MigrationWarning({
oldEntrypointName: "embeddings/minimax",
});
export * from "@langchain/community/embeddings/minimax";
| langchainjs/langchain/src/embeddings/minimax.ts/0 | {
"file_path": "langchainjs/langchain/src/embeddings/minimax.ts",
"repo_id": "langchainjs",
"token_count": 76
} | 980 |
import json
import os
from typing import Iterator, List, Optional, Union, Tuple
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.models import Unigram
from .base_tokenizer import BaseTokenizer
class SentencePieceUnigramTokenizer(BaseTokenizer):
... | tokenizers/bindings/python/py_src/tokenizers/implementations/sentencepiece_unigram.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/sentencepiece_unigram.py",
"repo_id": "tokenizers",
"token_count": 3351
} | 462 |
python_sources()
| llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-triton/llama_index/llms/nvidia_triton/BUILD/0 | {
"file_path": "llama_index/llama-index-integrations/llms/llama-index-llms-nvidia-triton/llama_index/llms/nvidia_triton/BUILD",
"repo_id": "llama_index",
"token_count": 6
} | 1,320 |
from langchain_community.tools.tavily_search.tool import (
TavilyAnswer,
TavilyInput,
TavilySearchResults,
)
__all__ = ["TavilyInput", "TavilySearchResults", "TavilyAnswer"]
| langchain/libs/langchain/langchain/tools/tavily_search/tool.py/0 | {
"file_path": "langchain/libs/langchain/langchain/tools/tavily_search/tool.py",
"repo_id": "langchain",
"token_count": 70
} | 562 |
// Copyright (C) 2019-2020 Zilliz. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable l... | milvus/internal/core/src/segcore/Collection.h/0 | {
"file_path": "milvus/internal/core/src/segcore/Collection.h",
"repo_id": "milvus",
"token_count": 537
} | 1,882 |
from langchain_community.agent_toolkits.openapi.base import create_openapi_agent
__all__ = ["create_openapi_agent"]
| langchain/libs/langchain/langchain/agents/agent_toolkits/openapi/base.py/0 | {
"file_path": "langchain/libs/langchain/langchain/agents/agent_toolkits/openapi/base.py",
"repo_id": "langchain",
"token_count": 38
} | 436 |
# HWP Loader
This loader reads the HWP file, which is the format of many official documents in South Korea.
## Usage
To use this loader, you need to pass in a file name. It's fine whether the file is compressed or not.
```python
from llama_hub.hangeul import HWPReader
from pathlib import Path
hwp_path = Path("/pat... | llama_index/llama-index-integrations/readers/llama-index-readers-hwp/README.md/0 | {
"file_path": "llama_index/llama-index-integrations/readers/llama-index-readers-hwp/README.md",
"repo_id": "llama_index",
"token_count": 130
} | 1,388 |
package allocator
type MockGIDAllocator struct {
Interface
AllocF func(count uint32) (UniqueID, UniqueID, error)
AllocOneF func() (UniqueID, error)
UpdateIDF func() error
}
func (m MockGIDAllocator) Alloc(count uint32) (UniqueID, UniqueID, error) {
return m.AllocF(count)
}
func (m MockGIDAllocator) AllocOne(... | milvus/internal/allocator/mock_global_id.go/0 | {
"file_path": "milvus/internal/allocator/mock_global_id.go",
"repo_id": "milvus",
"token_count": 206
} | 1,741 |
"""Pandas csv structured store."""
import logging
from typing import Any, Optional, Sequence
import pandas as pd
from llama_index.legacy.core.base_query_engine import BaseQueryEngine
from llama_index.legacy.core.base_retriever import BaseRetriever
from llama_index.legacy.data_structs.table import PandasStructTable
f... | llama_index/llama-index-legacy/llama_index/legacy/indices/struct_store/pandas.py/0 | {
"file_path": "llama_index/llama-index-legacy/llama_index/legacy/indices/struct_store/pandas.py",
"repo_id": "llama_index",
"token_count": 964
} | 1,605 |
from typing import Any, List, Optional, Sequence
from llama_index.core.prompts.prompt_utils import get_biggest_prompt
from llama_index.core.response_synthesizers.refine import Refine
from llama_index.core.types import RESPONSE_TEXT_TYPE
class CompactAndRefine(Refine):
"""Refine responses across compact text chun... | llama_index/llama-index-core/llama_index/core/response_synthesizers/compact_and_refine.py/0 | {
"file_path": "llama_index/llama-index-core/llama_index/core/response_synthesizers/compact_and_refine.py",
"repo_id": "llama_index",
"token_count": 853
} | 1,204 |
[build-system]
build-backend = "poetry.core.masonry.api"
requires = ["poetry-core"]
[tool.codespell]
check-filenames = true
check-hidden = true
skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
[tool.llamahub]
classes = ["StockMarketDataQueryEnginePack"]
contains_example = false
import_path = "llama_index.pack... | llama_index/llama-index-packs/llama-index-packs-stock-market-data-query-engine/pyproject.toml/0 | {
"file_path": "llama_index/llama-index-packs/llama-index-packs-stock-market-data-query-engine/pyproject.toml",
"repo_id": "llama_index",
"token_count": 708
} | 1,872 |
import importlib.metadata
import logging
import os
import traceback
import warnings
from contextvars import ContextVar
from typing import Any, Dict, List, Union, cast
from uuid import UUID
import requests
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.callbacks import BaseCallbackHandle... | langchain/libs/community/langchain_community/callbacks/llmonitor_callback.py/0 | {
"file_path": "langchain/libs/community/langchain_community/callbacks/llmonitor_callback.py",
"repo_id": "langchain",
"token_count": 10500
} | 213 |
<jupyter_start><jupyter_text>LanceDB Vector StoreIn this notebook we are going to show how to use [LanceDB](https://www.lancedb.com) to perform vector searches in LlamaIndex If you're opening this Notebook on colab, you will probably need to install LlamaIndex ๐ฆ.<jupyter_code>%pip install llama-index-vector-stores-lan... | llama_index/docs/examples/vector_stores/LanceDBIndexDemo.ipynb/0 | {
"file_path": "llama_index/docs/examples/vector_stores/LanceDBIndexDemo.ipynb",
"repo_id": "llama_index",
"token_count": 1216
} | 1,135 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/src/transformers/models/resnet/__init__.py/0 | {
"file_path": "transformers/src/transformers/models/resnet/__init__.py",
"repo_id": "transformers",
"token_count": 1299
} | 734 |
---
sidebar_position: 1
sidebar_label: String Evaluators
---
# String Evaluators
A string evaluator is a component within LangChain designed to assess the performance of a language model by comparing its generated outputs (predictions) to a reference string or an input. This comparison is a crucial step in the evalua... | langchainjs/docs/core_docs/docs/guides/evaluation/string/index.mdx/0 | {
"file_path": "langchainjs/docs/core_docs/docs/guides/evaluation/string/index.mdx",
"repo_id": "langchainjs",
"token_count": 465
} | 695 |
<jupyter_start><jupyter_text>E2B Data Analysis[E2B's cloud environments](https://e2b.dev) are great runtime sandboxes for LLMs.E2B's Data Analysis sandbox allows for safe code execution in a sandboxed environment. This is ideal for building tools such as code interpreters, or Advanced Data Analysis like in ChatGPT.E2B ... | langchain/docs/docs/integrations/tools/e2b_data_analysis.ipynb/0 | {
"file_path": "langchain/docs/docs/integrations/tools/e2b_data_analysis.ipynb",
"repo_id": "langchain",
"token_count": 2419
} | 182 |
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