text stringlengths 23 371k | source stringlengths 32 152 |
|---|---|
!--Copyright 2023 The GLIGEN Authors and 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 ap... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/stable_diffusion/gligen.md |
his notebook shows how to deploy a vision model from 🤗 Transformers (written in TensorFlow) to [Vertex AI](https://cloud.google.com/vertex-ai). This is beneficial in many ways:
* Vertex AI provides support for autoscaling, authorization, and authentication out of the box.
* One can maintain multiple versions of a mod... | huggingface/blog/blob/main/notebooks/112_vertex_ai_vision.ipynb |
Using PEFT with timm
`peft` allows us to train any model with LoRA as long as the layer type is supported. Since `Conv2D` is one of the supported layer types, it makes sense to test it on image models.
In this short notebook, we will demonstrate this with an image classification task using [`timm`](https://huggingfa... | huggingface/peft/blob/main/examples/image_classification/image_classification_timm_peft_lora.ipynb |
Gradio Demo: image_classifier_interface_load
```
!pip install -q gradio
```
```
# Downloading files from the demo repo
import os
!wget -q https://github.com/gradio-app/gradio/raw/main/demo/image_classifier_interface_load/cheetah1.jpeg
!wget -q https://github.com/gradio-app/gradio/raw/main/demo/image_classifier_in... | gradio-app/gradio/blob/main/demo/image_classifier_interface_load/run.ipynb |
!--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/tasks/monocular_depth_estimation.md |
--
title: "Retrieval Augmented Generation with Huggingface Transformers and Ray"
thumbnail: /blog/assets/12_ray_rag/ray_arch_updated.png
authors:
- user: ray-project
guest: true
---
# Retrieval Augmented Generation with Huggingface Transformers and Ray
##### A guest blog post by <a href="/amogkam">Amog Kamsetty</a... | huggingface/blog/blob/main/ray-rag.md |
@gradio/image
## 0.5.3
### Fixes
- [#6766](https://github.com/gradio-app/gradio/pull/6766) [`73268ee`](https://github.com/gradio-app/gradio/commit/73268ee2e39f23ebdd1e927cb49b8d79c4b9a144) - Improve source selection UX. Thanks [@hannahblair](https://github.com/hannahblair)!
## 0.5.2
### Patch Changes
- Updated ... | gradio-app/gradio/blob/main/js/image/CHANGELOG.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/peft/blob/main/docs/source/developer_guides/low_level_api.md |
--
title: Introducing Pull Requests and Discussions 🥳
thumbnail: /blog/assets/76_community_update/thumbnail.png
---
# Introducing Pull Requests and Discussions 🥳
We are thrilled to announce the release of our latest collab... | huggingface/blog/blob/main/community-update.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.
-->
# Collections
A collection is a group of related items on the Hub (models, datasets, Spaces, papers) that are organized together on the same page. Co... | huggingface/huggingface_hub/blob/main/docs/source/en/guides/collections.md |
Image classification
Image classification datasets are used to train a model to classify an entire image. There are a wide variety of applications enabled by these datasets such as identifying endangered wildlife species or screening for disease in medical images. This guide will show you how to apply transformations... | huggingface/datasets/blob/main/docs/source/image_classification.mdx |
--
title: "Introducing Agents.js: Give tools to your LLMs using JavaScript"
thumbnail: /blog/assets/agents-js/thumbnail.png
authors:
- user: nsarrazin
---
# Introducing Agents.js: Give tools to your LLMs using JavaScript
We have recently been working on Agents.js at [huggingface.js](https://github.com/huggingface/... | huggingface/blog/blob/main/agents-js.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/model_doc/univnet.md |
Advanced Topics
## Contents
- [Using OpenCV in Spaces](./spaces-using-opencv)
- [More ways to create Spaces](./spaces-more-ways-to-create)
- [Managing Spaces with Github Actions ](./spaces-github-actions)
- [Managing Spaces with CircleCI Workflows ](./spaces-circleci)
- [How to Add a Space to ArXiv ](./spaces-add-to... | huggingface/hub-docs/blob/main/docs/hub/spaces-advanced.md |
--
title: "Using Machine Learning to Aid Survivors and Race through Time"
thumbnail: /blog/assets/using-ml-for-disasters/thumbnail.png
authors:
- user: merve
- user: adirik
---
# Using Machine Learning to Aid Survivors and Race through Time
On February 6, 2023, earthquakes measuring 7.7 and 7.6 hit South Eastern Tu... | huggingface/blog/blob/main/using-ml-for-disasters.md |
Using spaCy at Hugging Face
`spaCy` is a popular library for advanced Natural Language Processing used widely across industry. `spaCy` makes it easy to use and train pipelines for tasks like named entity recognition, text classification, part of speech tagging and more, and lets you build powerful applications to pro... | huggingface/hub-docs/blob/main/docs/hub/spacy.md |
Würstchen text-to-image fine-tuning
## Running locally with PyTorch
Before running the scripts, make sure to install the library's training dependencies:
**Important**
To make sure you can successfully run the latest versions of the example scripts, we highly recommend **installing from source** and keeping the in... | huggingface/diffusers/blob/main/examples/wuerstchen/text_to_image/README.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/loading_overview.md |
--
language:
- en
license: mit
library_name: pytorch-lightning
tags:
- pytorch
- image-classification
datasets:
- beans
metrics:
- acc
---
# my-cool-model
## Model description
You can embed local or remote images using ``
| huggingface/huggingface_hub/blob/main/tests/fixtures/cards/sample_simple.md |
Gradio Demo: latex
```
!pip install -q gradio
```
```
import gradio as gr
with gr.Blocks() as demo:
gr.Markdown(
r"""
# Hello World! $\frac{\sqrt{x + y}}{4}$ is today's lesson
## the $\sqrt{x + y}$ is first
Start with $\frac{\frac{x+1}{x+2}}{x+3}$ then we get $ 2+x $ and $3$.
There... | gradio-app/gradio/blob/main/demo/latex/run.ipynb |
Beam Datasets
Some datasets are too large to be processed on a single machine. Instead, you can process them with [Apache Beam](https://beam.apache.org/), a library for parallel data processing. The processing pipeline is executed on a distributed processing backend such as [Apache Flink](https://flink.apache.org/), ... | huggingface/datasets/blob/main/docs/source/beam.mdx |
Gradio Demo: video_identity
```
!pip install -q gradio
```
```
# Downloading files from the demo repo
import os
os.mkdir('video')
!wget -q -O video/video_sample.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_identity/video/video_sample.mp4
```
```
import gradio as gr
import os
def video_identity... | gradio-app/gradio/blob/main/demo/video_identity/run.ipynb |
--
title: "Accelerating PyTorch Transformers with Intel Sapphire Rapids - part 2"
thumbnail: /blog/assets/129_intel_sapphire_rapids_inference/01.png
authors:
- user: juliensimon
---
# Accelerating PyTorch Transformers with Intel Sapphire Rapids, part 2
In a [recent post](https://huggingface.co/blog/intel-sapphire-ra... | huggingface/blog/blob/main/intel-sapphire-rapids-inference.md |
@gradio/fallback
## 0.2.6
### Patch Changes
- Updated dependencies [[`828fb9e`](https://github.com/gradio-app/gradio/commit/828fb9e6ce15b6ea08318675a2361117596a1b5d), [`73268ee`](https://github.com/gradio-app/gradio/commit/73268ee2e39f23ebdd1e927cb49b8d79c4b9a144)]:
- @gradio/statustracker@0.4.3
- @gradio/atoms... | gradio-app/gradio/blob/main/js/fallback/CHANGELOG.md |
Access and view Metrics
Hugging Face Endpoints provides access to the metrics and analytics of your Endpoints through the UI on the detailed overview in the “Analytics” tab of your Endpoints.
<img src="https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/10_metric.png" alt="metric da... | huggingface/hf-endpoints-documentation/blob/main/docs/source/guides/metrics.mdx |
🚀 Creating Discord Bots from Gradio Apps 🚀
Tags: NLP, TEXT, CHAT
We're excited to announce that Gradio can now automatically create a discord bot from a deployed app! 🤖
Discord is a popular communication platform that allows users to chat and interact with each other in real-time. By turning your Gradio app into... | gradio-app/gradio/blob/main/guides/04_chatbots/03_creating-a-discord-bot-from-a-gradio-app.md |
MobileNet v2
**MobileNetV2** is a convolutional neural network architecture that seeks to perform well on mobile devices. It is based on an [inverted residual structure](https://paperswithcode.com/method/inverted-residual-block) where the residual connections are between the bottleneck layers. The intermediate expan... | huggingface/pytorch-image-models/blob/main/docs/models/mobilenet-v2.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/model_doc/donut.md |
Gradio Demo: blocks_essay
```
!pip install -q gradio
```
```
import gradio as gr
countries_cities_dict = {
"USA": ["New York", "Los Angeles", "Chicago"],
"Canada": ["Toronto", "Montreal", "Vancouver"],
"Pakistan": ["Karachi", "Lahore", "Islamabad"],
}
def change_textbox(choice):
if choice == "s... | gradio-app/gradio/blob/main/demo/blocks_essay/run.ipynb |
!--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/schedulers/ddim_inverse.md |
Gradio Demo: generate_tone
```
!pip install -q gradio numpy
```
```
import numpy as np
import gradio as gr
notes = ["C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"]
def generate_tone(note, octave, duration):
sr = 48000
a4_freq, tones_from_a4 = 440, 12 * (octave - 4) + (note - 9)
frequ... | gradio-app/gradio/blob/main/demo/generate_tone/run.ipynb |
--
title: Getting Started with Hugging Face Inference Endpoints
thumbnail: /blog/assets/109_inference_endpoints/endpoints05.png
authors:
- user: juliensimon
---
# Getting Started with Hugging Face Inference Endpoints
Training machine learning models has become quite simple, especially with the rise of pre-trained mo... | huggingface/blog/blob/main/inference-endpoints.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/self_attention_guidance.md |
`@gradio/form`
```html
<script>
import { Form } from "@gradio/form";
</script>
```
Form
```javascript
export let visible = true;
export let scale: number | null = null;
export let min_width = 0;
```
| gradio-app/gradio/blob/main/js/form/README.md |
--
title: "Non-engineers guide: Train a LLaMA 2 chatbot"
thumbnail: /blog/assets/78_ml_director_insights/tuto.png
authors:
- user: 2legit2overfit
- user: abhishek
---
# Non-engineers guide: Train a LLaMA 2 chatbot
## Introduction
In this tutorial we will show you how anyone can build their own open-source ChatGPT w... | huggingface/blog/blob/main/Llama2-for-non-engineers.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/tutorials/creating_a_scene.mdx |
# [Deprecated] Multi Token Textual Inversion
**IMPORTART: This research project is deprecated. Multi Token Textual Inversion is now supported natively in [the official textual inversion example](https://github.com/huggingface/diffusers/tree/main/examples/textual_inversion#running-locally-with-pytorch).**
The author o... | huggingface/diffusers/blob/main/examples/research_projects/multi_token_textual_inversion/README.md |
Gradio Demo: hello_world_3
```
!pip install -q gradio
```
```
import gradio as gr
def greet(name, is_morning, temperature):
salutation = "Good morning" if is_morning else "Good evening"
greeting = f"{salutation} {name}. It is {temperature} degrees today"
celsius = (temperature - 32) * 5 / 9
retur... | gradio-app/gradio/blob/main/demo/hello_world_3/run.ipynb |
ou are at the right place if you want to understand what the Byte pair Encoding subword tokenization algorithm is, how to train it and how the tokenization of a text is done with this algorithm. The BPE algorithm was initially proposed as a text compression algorithm but it is also very well suited as a tokenizer for y... | huggingface/course/blob/main/subtitles/en/raw/chapter6/06_bpe.md |
Conclusion
Congrats on finishing this unit! You’ve just trained your first ML-Agents and shared it to the Hub 🥳.
The best way to learn is to **practice and try stuff**. Why not try another environment? [ML-Agents has 18 different environments](https://github.com/Unity-Technologies/ml-agents/blob/develop/docs/Learni... | huggingface/deep-rl-class/blob/main/units/en/unit5/conclusion.mdx |
Load image data
Image datasets have [`Image`] type columns, which contain PIL objects.
<Tip>
To work with image datasets, you need to have the `vision` dependency installed. Check out the [installation](./installation#vision) guide to learn how to install it.
</Tip>
When you load an image dataset and call the im... | huggingface/datasets/blob/main/docs/source/image_load.mdx |
EfficientNet (Knapsack Pruned)
**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 ... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/efficientnet-pruned.mdx |
!--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/latent_diffusion.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/ibert.md |
--
title: "Ethical Guidelines for developing the Diffusers library"
thumbnail: /blog/assets/ethics-diffusers/thumbnail.png
authors:
- user: giadap
---
# Ethical guidelines for developing the Diffusers library
We are on a journey to make our libraries more responsible, one commit at a time!
As part of the [Diffuser... | huggingface/blog/blob/main/ethics-diffusers.md |
Audit Logs
<Tip warning={true}>
This feature is part of the <a href="https://huggingface.co/enterprise" target="_blank">Enterprise Hub</a>.
</Tip>
Audit Logs enable organization admins to easily review actions taken by members, including organization membership, repository settings and billing changes.
Audit Logs a... | huggingface/hub-docs/blob/main/docs/hub/audit-logs.md |
Gradio Components: The Key Concepts
In this section, we discuss a few important concepts when it comes to components in Gradio.
It's important to understand these concepts when developing your own component.
Otherwise, your component may behave very different to other Gradio components!
Tip: You can skip this secti... | gradio-app/gradio/blob/main/guides/05_custom-components/02_key-component-concepts.md |
--
title: "Introducing BERTopic Integration with the Hugging Face Hub"
thumbnail: /blog/assets/145_bertopic/logo.png
authors:
- user: MaartenGr
guest: true
- user: davanstrien
---
# Introducing BERTopic Integration with the Hugging Face Hub
[; 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/vit.md |
ome bugs in your code are very straightforward. You try running it, you get a syntax error somewhere, Python tells you exactly where, and you fix it. This is great - it's simple and satisfying. Sometimes, though, things crash and the error is impossible to understand. This happens a lot in machine learning for a few re... | huggingface/course/blob/main/subtitles/en/raw/chapter8/04_debug-tf.md |
!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/speech_to_text_2.md |
--
title: "OpenRAIL: Towards open and responsible AI licensing frameworks"
thumbnail: /blog/assets/100_open_rail/100_open-rail.png
authors:
- user: CarlosMF
---
# OpenRAIL: Towards open and responsible AI licensing frameworks
Open & Responsible AI licenses ("OpenRAIL") are AI-specific licenses enabling open acce... | huggingface/blog/blob/main/open_rail.md |
--
title: Using LoRA for Efficient Stable Diffusion Fine-Tuning
thumbnail: /blog/assets/lora/thumbnail.png
authors:
- user: pcuenq
- user: sayakpaul
---
# Using LoRA for Efficient Stable Diffusion Fine-Tuning
[LoRA: Low-Rank Adaptation of Large Language Models](https://arxiv.org/abs/2106.09685) is a novel technique ... | huggingface/blog/blob/main/lora.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/tutorials/using_peft_for_inference.md |
Metric Card for Recall
## Metric Description
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the number of true positives and FN is the number of false negatives.
## How to Use
At minim... | huggingface/datasets/blob/main/metrics/recall/README.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/pad_truncation.md |
Real Time Speech Recognition
Tags: ASR, SPEECH, STREAMING
## Introduction
Automatic speech recognition (ASR), the conversion of spoken speech to text, is a very important and thriving area of machine learning. ASR algorithms run on practically every smartphone, and are becoming increasingly embedded in professional... | gradio-app/gradio/blob/main/guides/09_other-tutorials/real-time-speech-recognition.md |
Consistency Decoder
Consistency decoder can be used to decode the latents from the denoising UNet in the [`StableDiffusionPipeline`]. This decoder was introduced in the [DALL-E 3 technical report](https://openai.com/dall-e-3).
The original codebase can be found at [openai/consistencydecoder](https://github.com/open... | huggingface/diffusers/blob/main/docs/source/en/api/models/consistency_decoder_vae.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 a... | huggingface/transformers/blob/main/examples/pytorch/text-classification/README.md |
# Amused training
Amused can be finetuned on simple datasets relatively cheaply and quickly. Using 8bit optimizers, lora, and gradient accumulation, amused can be finetuned with as little as 5.5 GB. Here are a set of examples for finetuning amused on some relatively simple datasets. These training recipies are aggress... | huggingface/diffusers/blob/main/examples/amused/README.md |
--
title: Mean IoU
emoji: 🤗
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
tags:
- evaluate
- metric
description: >-
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and t... | huggingface/evaluate/blob/main/metrics/mean_iou/README.md |
--
title: SuperGLUE
emoji: 🤗
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
tags:
- evaluate
- metric
description: >-
SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, improved... | huggingface/evaluate/blob/main/metrics/super_glue/README.md |
(Tensorflow) 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://paper... | huggingface/pytorch-image-models/blob/main/docs/models/tf-inception-v3.md |
``python
import os
import torch
from transformers import (
AutoTokenizer,
default_data_collator,
AutoModelForSeq2SeqLM,
Seq2SeqTrainingArguments,
Seq2SeqTrainer,
GenerationConfig,
)
from peft import get_peft_model, PromptTuningInit, PromptTuningConfig, TaskType
from datasets import load_dataset... | huggingface/peft/blob/main/examples/conditional_generation/peft_prompt_tuning_seq2seq_with_generate.ipynb |
DenseNet
**DenseNet** is a type of convolutional neural network that utilises dense connections between layers, through [Dense Blocks](http://www.paperswithcode.com/method/dense-block), where we connect *all layers* (with matching feature-map sizes) directly with each other. To preserve the feed-forward nature, each ... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/densenet.mdx |
# Diffusers examples with Intel optimizations
**This research project is not actively maintained by the diffusers team. For any questions or comments, please make sure to tag @hshen14 .**
This aims to provide diffusers examples with Intel optimizations such as Bfloat16 for training/fine-tuning acceleration and 8-bit ... | huggingface/diffusers/blob/main/examples/research_projects/intel_opts/README.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/index.mdx |
Dataset features
[`Features`] defines the internal structure of a dataset. It is used to specify the underlying serialization format. What's more interesting to you though is that [`Features`] contains high-level information about everything from the column names and types, to the [`ClassLabel`]. You can think of [`F... | huggingface/datasets/blob/main/docs/source/about_dataset_features.mdx |
🧨 Diffusers Experimental
We are adding experimental code to support novel applications and usages of the Diffusers library.
Currently, the following experiments are supported:
* Reinforcement learning via an implementation of the [Diffuser](https://arxiv.org/abs/2205.09991) model. | huggingface/diffusers/blob/main/src/diffusers/experimental/README.md |
How to write a good issue[[how-to-write-a-good-issue]]
<CourseFloatingBanner chapter={8}
classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/en/chapter8/section5.ipynb"},
{label: "Aws Studio... | huggingface/course/blob/main/chapters/en/chapter8/5.mdx |
Gradio Demo: unified_demo_text_generation
```
!pip install -q gradio torch transformers
```
```
import gradio as gr
from transformers import pipeline
generator = pipeline('text-generation', model = 'gpt2')
def generate_text(text_prompt):
response = generator(text_prompt, max_length = 30, num_return_sequences=5... | gradio-app/gradio/blob/main/demo/unified_demo_text_generation/run.ipynb |
Gradio Demo: calculator_blocks_cached
```
!pip install -q gradio
```
```
import gradio as gr
def calculator(num1, operation, num2):
if operation == "add":
return num1 + num2
elif operation == "subtract":
return num1 - num2
elif operation == "multiply":
return num1 * num2
... | gradio-app/gradio/blob/main/demo/calculator_blocks_cached/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/efficientformer.md |
Spaces Overview
Hugging Face Spaces make it easy for you to create and deploy ML-powered demos in minutes. Watch the following video for a quick introduction to Spaces:
<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/3bSVKNKb_PY" title="Spaces intro" frameborder="0" allow="accelerometer;... | huggingface/hub-docs/blob/main/docs/hub/spaces-overview.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/tasks/visual_question_answering.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/training/dreambooth.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/optimum/blob/main/docs/source/exporters/tflite/usage_guides/contribute.mdx |
!--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/normalization.md |
!---
Copyright 2021 The Google Flax Team Authors and 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 re... | huggingface/transformers/blob/main/examples/flax/text-classification/README.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/model_doc/patchtst.md |
Gradio Demo: image-simple
```
!pip install -q gradio
```
```
# Downloading files from the demo repo
import os
!wget -q https://github.com/gradio-app/gradio/raw/main/demo/image-simple/cheetah.jpg
```
```
import gradio as gr
def image(im):
return im
with gr.Blocks() as demo:
im = gr.Image()
im2 = ... | gradio-app/gradio/blob/main/demo/image-simple/run.ipynb |
oading a custom dataset. Although the Hugging Face Hub hosts over a thousand public datasets, you'll often need to work with data that is stored on your laptop or some remote server. In this video we'll explore how the Datasets library can be used to load datasets that aren’t available on the Hugging Face Hub. As you c... | huggingface/course/blob/main/subtitles/en/raw/chapter5/02_custom-dataset.md |
`@gradio/imageeditor`
| gradio-app/gradio/blob/main/js/imageeditor/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 a... | huggingface/transformers/blob/main/README_ko.md |
Search
You can now easily search anything on the Hub with **Full-text search**. We index model cards, dataset cards, and Spaces app.py files.
Go directly to https://huggingface.co/search or, using the search bar at the top of https://huggingface.co, you can select "Try Full-text search" to help find what you seek on... | huggingface/hub-docs/blob/main/docs/hub/search.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/perf_train_cpu_many.md |
Gradio Demo: chatbot_multimodal
```
!pip install -q gradio
```
```
# Downloading files from the demo repo
import os
!wget -q https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/avatar.png
```
```
import gradio as gr
import os
import time
# Chatbot demo with multimodal input (text, markdown, L... | gradio-app/gradio/blob/main/demo/chatbot_multimodal/run.ipynb |
DuckDB
[DuckDB](https://duckdb.org/docs/) is a database that supports reading and querying Parquet files really fast. Begin by creating a connection to DuckDB, and then install and load the [`httpfs`](https://duckdb.org/docs/extensions/httpfs.html) extension to read and write remote files:
<inferencesnippet>
<python... | huggingface/datasets-server/blob/main/docs/source/duckdb.mdx |
!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/matcha.md |
--
title: "Graph Classification with Transformers"
thumbnail: /blog/assets/125_intro-to-graphml/thumbnail_classification.png
---
# Graph classification with Transformers
<div class="blog-metadata">
<small>Published April 14, 2023.</small>
<a target="_blank" class="btn no-underline text-sm mb-5 font-sans" hre... | huggingface/blog/blob/main/graphml-classification.md |
--
title: Fine-Tune a Semantic Segmentation Model with a Custom Dataset
thumbnail: /blog/assets/56_fine_tune_segformer/thumb.png
authors:
- user: segments-tobias
guest: true
- user: nielsr
---
# Fine-Tune a Semantic Segmentation Model with a Custom Dataset
<script async defer src="https://unpkg.com/medium-zoom-ele... | huggingface/blog/blob/main/fine-tune-segformer.md |
Metric Card for GLUE
## Metric description
This metric is used to compute the GLUE evaluation metric associated to each [GLUE dataset](https://huggingface.co/datasets/glue).
GLUE, the General Language Understanding Evaluation benchmark is a collection of resources for training, evaluating, and analyzing natural lan... | huggingface/datasets/blob/main/metrics/glue/README.md |
!--Copyright 2022 The HuggingFace Team and The OpenBMB 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... | huggingface/transformers/blob/main/docs/source/en/model_doc/cpmant.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/model_doc/dinov2.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/tasks/idefics.md |
--
[]
---
# invalid-card-data
This card should fail when trying to load it in because the card data between the `---` is a list instead of a dict.
| huggingface/huggingface_hub/blob/main/tests/fixtures/cards/sample_invalid_card_data.md |
🤗 Transformers
To run the 🤗 Transformers examples make sure you have installed the following libraries:
```bash
pip install datasets transformers torch evaluate nltk rouge_score
```
## Trainer
The metrics in `evaluate` can be easily integrated with the [`~transformers.Trainer`]. The `Trainer` accepts a `compute_... | huggingface/evaluate/blob/main/docs/source/transformers_integrations.mdx |
Summary[[summary]]
<CourseFloatingBanner
chapter={1}
classNames="absolute z-10 right-0 top-0"
/>
In this chapter, you saw how to approach different NLP tasks using the high-level `pipeline()` function from 🤗 Transformers. You also saw how to search for and use models in the Hub, as well as how to use the In... | huggingface/course/blob/main/chapters/en/chapter1/9.mdx |
Training Examples
## EfficientNet-B2 with RandAugment - 80.4 top-1, 95.1 top-5
These params are for dual Titan RTX cards with NVIDIA Apex installed:
`./distributed_train.sh 2 /imagenet/ --model efficientnet_b2 -b 128 --sched step --epochs 450 --decay-epochs 2.4 --decay-rate .97 --opt rmsproptf --opt-eps .001 -j 8 --... | huggingface/pytorch-image-models/blob/main/docs/training_hparam_examples.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 a... | huggingface/transformers/blob/main/README.md |
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.