text stringlengths 23 371k | source stringlengths 32 152 |
|---|---|
--
title: NIST_MT
emoji: 🤗
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
tags:
- evaluate
- metric
- machine-translation
description:
DARPA commissioned NIST to develop an MT evaluation facility based on the BLEU score.
---
# Metric Card for NIST's MT metric
## Me... | huggingface/evaluate/blob/main/metrics/nist_mt/README.md |
SSL ResNet
**Residual Networks**, or **ResNets**, learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. Instead of hoping each few stacked layers directly fit a desired underlying mapping, residual nets let these layers fit a residual mapping. They stack [residual bl... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/ssl-resnet.mdx |
--
title: What's new in Diffusers? 🎨
thumbnail: /blog/assets/102_diffusers_2nd_month/inpainting.png
authors:
- user: osanseviero
---
# What's new in Diffusers? 🎨
A month and a half ago we released `diffusers`, a library that provides a modular toolbox for diffusion models across modalities. A couple of weeks later... | huggingface/blog/blob/main/diffusers-2nd-month.md |
Adversarial Inception v3
**Inception v3** is a convolutional neural network architecture from the Inception family that makes several improvements including using [Label Smoothing](https://paperswithcode.com/method/label-smoothing), Factorized 7 x 7 convolutions, and the use of an [auxiliary classifer](https://papers... | huggingface/pytorch-image-models/blob/main/docs/models/adversarial-inception-v3.md |
`@gradio/code`
```html
<script>
import { BaseCode, BaseCopy, BaseDownload, BaseWidget, BaseExample} from "gradio/code";
</script>
```
BaseCode
```javascript
export let classNames = "";
export let value = "";
export let dark_mode: boolean;
export let basic = true;
export let language: string;
export let li... | gradio-app/gradio/blob/main/js/code/README.md |
!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# 安装
在开始之前，您需要通过安装适当的软件包来设置您的环境
huggingface_hub 在 Python 3.8 或更高版本上进行了测试，可以保证在这些版本上正常运行。如果您使用的是 Python 3.7 或更低版本，可能会出现兼容性问题
## 使用 pip 安装
我们建议将hugg... | huggingface/huggingface_hub/blob/main/docs/source/cn/installation.md |
p align="center">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/datasets/safetensors/assets/raw/main/banner-dark.svg">
<source media="(prefers-color-scheme: light)" srcset="https://huggingface.co/datasets/safetensors/assets/raw/main/banner-light.svg">
<img alt="Hugg... | huggingface/safetensors/blob/main/README.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/model_doc/auto.md |
Gradio Demo: gif_maker
```
!pip install -q gradio opencv-python
```
```
import cv2
import gradio as gr
def gif_maker(img_files):
img_array = []
for filename in img_files:
img = cv2.imread(filename.name)
height, width, _ = img.shape
size = (width,height)
img_array.append(img... | gradio-app/gradio/blob/main/demo/gif_maker/run.ipynb |
SWSL ResNet
**Residual Networks**, or **ResNets**, learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. Instead of hoping each few stacked layers directly fit a desired underlying mapping, residual nets let these layers fit a residual mapping. They stack [residual b... | huggingface/pytorch-image-models/blob/main/docs/models/swsl-resnet.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/model_doc/camembert.md |
(Tensorflow) EfficientNet
**EfficientNet** is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a *compound coefficient*. Unlike conventional practice that arbitrary scales these factors, the EfficientNet scaling method uniformly scale... | huggingface/pytorch-image-models/blob/main/docs/models/tf-efficientnet.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/using-diffusers/reusing_seeds.md |
--
{card_data}
---
# {{ pretty_name | default("Dataset Name", true)}}
{{ some_data }}
| huggingface/huggingface_hub/blob/main/tests/fixtures/cards/sample_datasetcard_template.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/using-diffusers/distilled_sd.md |
Datasets server API - search service
> /search endpoint
> /filter endpoint
## Configuration
The service can be configured using environment variables. They are grouped by scope.
### Duckdb index full text search
- `DUCKDB_INDEX_CACHE_DIRECTORY`: directory where the temporal duckdb index files are downloaded. Defau... | huggingface/datasets-server/blob/main/services/search/README.md |
# Token classification
Based on the scripts [`run_ner.py`](https://github.com/huggingface/transformers/blob/main/examples/legacy/token-classification/run_ner.py).
The following examples are covered in this section:
* NER on the GermEval 2014 (German NER) dataset
* Emerging and Rare Entities task: WNUT’17 (English NE... | huggingface/transformers/blob/main/examples/legacy/token-classification/README.md |
hat is domain adaptation? When fine-tuning a pretrained model on a new dataset, the fine-tuned model we obtain will make predictions that are attuned to this new dataset. When the two models are trained with the same task, we can then compare their predictions on the same input. The predictions of the two models will b... | huggingface/course/blob/main/subtitles/en/raw/chapter7/03c_domain-adaptation.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/tasks/audio_classification.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/model_doc/bertweet.md |
Gradio Demo: file_explorer_component_events
```
!pip install -q gradio
```
```
# Downloading files from the demo repo
import os
os.mkdir('dir1')
!wget -q -O dir1/bar.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir1/bar.txt
!wget -q -O dir1/foo.txt https://github.com/gradi... | gradio-app/gradio/blob/main/demo/file_explorer_component_events/run.ipynb |
--
title: "Announcing the Hugging Face Fellowship Program"
thumbnail: /blog/assets/62_fellowship/fellowship-thumbnail.png
authors:
- user: merve
- user: espejelomar
---
# Announcing the Hugging Face Fellowship Program
The Fellowship is a network of exceptional people from different backgrounds who contribute to the... | huggingface/blog/blob/main/fellowship.md |
Moderation
<Tip>
Check out the [Code of Conduct](https://huggingface.co/code-of-conduct) and the [Content Guidelines](https://huggingface.co/content-guidelines).
</Tip>
## Reporting a repository
To report a repository, you can click the three dots at the top right of a repository. Afterwards, you can click "Repor... | huggingface/hub-docs/blob/main/docs/hub/moderation.md |
!--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 ... | huggingface/simulate/blob/main/docs/source/api/joints.mdx |
Livebook on Spaces
**Livebook** is an open-source tool for writing interactive code notebooks in [Elixir](https://elixir-lang.org/). It's part of a growing collection of Elixir tools for [numerical computing](https://github.com/elixir-nx/nx), [data science](https://github.com/elixir-nx/explorer), and [Machine Learnin... | huggingface/hub-docs/blob/main/docs/hub/spaces-sdks-docker-livebook.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/generation_strategies.md |
Gradio Demo: stream_audio
```
!pip install -q gradio
```
```
import gradio as gr
import numpy as np
import time
def add_to_stream(audio, instream):
time.sleep(1)
if audio is None:
return gr.Audio(), instream
if instream is None:
ret = audio
else:
ret = (audio[0], np.concat... | gradio-app/gradio/blob/main/demo/stream_audio/run.ipynb |
ESE-VoVNet
**VoVNet** is a convolutional neural network that seeks to make [DenseNet](https://paperswithcode.com/method/densenet) more efficient by concatenating all features only once in the last feature map, which makes input size constant and enables enlarging new output channel.
Read about [one-shot aggregation... | huggingface/pytorch-image-models/blob/main/docs/models/ese-vovnet.md |
--
title: "How 🤗 Accelerate runs very large models thanks to PyTorch"
thumbnail: /blog/assets/104_accelerate-large-models/thumbnail.png
authors:
- user: sgugger
---
# How 🤗 Accelerate runs very large models thanks to PyTorch
## Load and run large models
Meta AI and BigScience recently open-sourced very large lang... | huggingface/blog/blob/main/accelerate-large-models.md |
Datasets server databases migrations
> Scripts to migrate the datasets server databases
## Configuration
The script can be configured using environment variables. They are grouped by scope.
### Migration script
Set environment variables to configure the job (`DATABASE_MIGRATIONS_` prefix):
- `DATABASE_MIGRATIONS... | huggingface/datasets-server/blob/main/jobs/mongodb_migration/README.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/main_classes/pipelines.md |
!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# 🤗 Hub 客户端库
通过`huggingface_hub` 库，您可以与面向机器学习开发者和协作者的平台 [Hugging Face Hub](https://huggingface.co/)进行交互，找到适用于您所在项目的预训练模型和数据集，体验在平台托管的数百个机器学习应用，还可以创建... | huggingface/huggingface_hub/blob/main/docs/source/cn/index.md |
Gradio Demo: gallery_selections
```
!pip install -q gradio
```
```
import gradio as gr
import numpy as np
with gr.Blocks() as demo:
imgs = gr.State()
gallery = gr.Gallery(allow_preview=False)
def deselect_images():
return gr.Gallery(selected_index=None)
def generate_images():
im... | gradio-app/gradio/blob/main/demo/gallery_selections/run.ipynb |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/model_doc/clipseg.md |
Gradio Demo: stream_asr
```
!pip install -q gradio torch torchaudio transformers
```
```
import gradio as gr
from transformers import pipeline
import numpy as np
transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")
def transcribe(stream, new_chunk):
sr, y = new_chunk
y =... | gradio-app/gradio/blob/main/demo/stream_asr/run.ipynb |
his demo takes in 12 inputs from the user in dropdowns and sliders and predicts income. It also has a separate button for explaining the prediction. | gradio-app/gradio/blob/main/demo/xgboost-income-prediction-with-explainability/DESCRIPTION.md |
Installation
Before you start, you'll need to setup your environment and install the appropriate packages. 🤗 Datasets is tested on **Python 3.7+**.
<Tip>
If you want to use 🤗 Datasets with TensorFlow or PyTorch, you'll need to install them separately. Refer to the [TensorFlow installation page](https://www.tensor... | huggingface/datasets/blob/main/docs/source/installation.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/value_guided_sampling.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/model_doc/bert.md |
`@gradio/label`
```html
<script>
import { BaseLabel } from "@gradio/label";
</script>
```
BaseLabel
```javascript
export let value: {
label?: string;
confidences?: { label: string; confidence: number }[];
};
export let color: string | undefined = undefined;
export let selectable = false;
```
| gradio-app/gradio/blob/main/js/label/README.md |
Contributing a Guide
Want to help teach Gradio? Consider contributing a Guide! 🤗
Broadly speaking, there are two types of guides:
- **Use cases**: guides that cover step-by-step how to build a particular type of machine learning demo or app using Gradio. Here's an example: [_Creating a Chatbot_](https://github.com... | gradio-app/gradio/blob/main/guides/cn/CONTRIBUTING.md |
(Gluon) Xception
**Xception** is a convolutional neural network architecture that relies solely on [depthwise separable convolution](https://paperswithcode.com/method/depthwise-separable-convolution) layers.
The weights from this model were ported from [Gluon](https://cv.gluon.ai/model_zoo/classification.html).
## ... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/gloun-xception.mdx |
alculate taxes using Textbox, Radio, and Dataframe components | gradio-app/gradio/blob/main/demo/tax_calculator/DESCRIPTION.md |
--
title: 'The Partnership: Amazon SageMaker and Hugging Face'
thumbnail: /blog/assets/17_the_partnership_amazon_sagemaker_and_hugging_face/thumbnail.png
---
<img src="/blog/assets/17_the_partnership_amazon_sagemaker_and_hugging_face/cover.png" alt="hugging-face-and-aws-logo" class="w-full">
> Look at these smiles!
... | huggingface/blog/blob/main/the-partnership-amazon-sagemaker-and-hugging-face.md |
!--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 ... | huggingface/transformers/blob/main/docs/source/en/torchscript.md |
--
title: "Introducing Optimum: The Optimization Toolkit for Transformers at Scale"
authors:
- user: mfuntowicz
- user: echarlaix
- user: michaelbenayoun
- user: jeffboudier
---
# Introducing 🤗 Optimum: The Optimization Toolkit for Transformers at Scale
This post is the first step of a journey for Hugging Face to ... | huggingface/blog/blob/main/hardware-partners-program.md |
Gradio Demo: json_component
```
!pip install -q gradio
```
```
import gradio as gr
with gr.Blocks() as demo:
gr.JSON(value={"Key 1": "Value 1", "Key 2": {"Key 3": "Value 2", "Key 4": "Value 3"}, "Key 5": ["Item 1", "Item 2", "Item 3"]})
demo.launch()
```
| gradio-app/gradio/blob/main/demo/json_component/run.ipynb |
Subsets and Splits
Transformers Source Texts
This query retrieves specific examples from the dataset related to transformers, providing a limited view of the data with basic filtering.