modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k |
|---|---|---|---|---|---|---|
Chun/w-en2zh-hsk | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
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"no_repeat_ngram_size... | 1 | null | ---
language: ro
inference: true
license: apache-2.0
tags:
- romanian
- seq2seq
- t5
---
This is the fine-tuned [mt5-base-romanian](https://huggingface.co/dumitrescustefan/mt5-base-romanian) base model (**390M** parameters).
The model was fine-tuned on the [romanian diacritics dataset](https://huggingface.co/dataset... |
Chun/w-en2zh-otm | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
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},
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"no_re... | 7 | null | ---
language:
- es
license: apache-2.0
tags:
- "longformer"
- "national library of spain"
- "spanish"
- "bne"
datasets:
- "bne"
widget:
- text: "David Broncano es un presentador de La <mask>."
- text: "Gracias a los datos de la BNE se ha podido <mask> este modelo del lenguaje."
- text: "Hay base legal dentr... |
Chun/w-zh2en-hsk | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
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"no_repeat_ngram_size... | 3 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluste... |
Chun/w-zh2en-mtm | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
tags:
- fastai
---
# Amazing!
🥳 Congratulations on hosting your fastai model on the Hugging Face Hub!
# Some next steps
1. Fill out this model card with more information (see the template below and the [documentation here](https://huggingface.co/docs/hub/model-repos))!
2. Create a demo in Gradio or Streamlit u... |
Chungu424/repodata | [] | null | {
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"num_beams... | 0 | 2022-11-02T16:03:00Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-xsum-B
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-... |
Chuu/Chumar | [] | null | {
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"num_beams... | 0 | 2022-11-02T16:06:41Z | ---
license: cc-by-nc-4.0
---
# **Our Mission for embedded AI**
In our mission to unleash AI on the edge, Datakalab has applied its proprietary quantization method on classical model architectures and converted everything to run in .rtm format for seamless compatibility with NXP® hardware, such as **I.MX 8M Plus®** ... |
Ci/Pai | [] | null | {
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},
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"min_length": null,
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"num_beams... | 0 | null | ---
language: code
tags:
- code
- gpt2
- generation
datasets:
- giulio98/xlcost-single-prompt
widget:
- text: "'''\nfunction to add two numbers\n'''\n###\n"
example_title: "add two numbers"
model-index:
- name: codegen-350M-multi-xlcost
results:
- task:
name: Code Generation
type: code-generation
... |
Ciruzzo/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
config: PAN-X.de
split: train
... |
Clarianliz30/Caitlyn | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- vision
- image-classification
datasets:
- mnist
---
# ZenML Community Hour Demo
This model is deployed using zenml framework, it goes from local deployment with mlflow to huggingface deployment!
## Model description
This is a mnist datatset trained using keras framework
## Intended uses... |
Clint/clinton | [] | null | {
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"num_beams... | 0 | null | ---
license: cc-by-nc-4.0
---
# **Our Mission for embedded AI**
In our mission to unleash AI on the edge, Datakalab has applied its proprietary quantization method on classical
architecture and converted everythong to run in ONNX format for seamless compatibility with many hardware such as :
- Intel
- Nvidia
- NXP... |
CoachCarter/distilbert-base-uncased-finetuned-squad | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
tags:
- spacy
- floret
- fasttext
- feature-extraction
- token-classification
language:
- tr
license: cc-by-sa-4.0
model-index:
- name: tr_vectors_web_md
results:
- task:
name: NMT
type: token-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.1112
---
Medium sized... |
CodeMonkey98/distilroberta-base-finetuned-wikitext2 | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remov... |
CodeNinja1126/bert-p-encoder | [
"pytorch"
] | null | {
"architectures": null,
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xlsr-53-mn-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove ... |
CodeNinja1126/bert-q-encoder | [
"pytorch"
] | null | {
"architectures": null,
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: roberta-finetuned-location
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-f... |
CoderBoy432/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 11 | null | ---
license: mit
---
### Iridescent Photo Style on Stable Diffusion
This is the 'iridescent-photo-style' concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptu... |
CoderEFE/DialoGPT-marxbot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"has_space"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
license: mit
---
### Chictof on Stable Diffusion via Dreambooth
#### model by ChicoTofu
This your the Stable Diffusion model fine-tuned the Chictof concept taught to Stable Diffusion with Dreambooth.
It can be used by modifying the `instance_prompt`: **a photo of sks chicto_tstp**
You can also train your own conce... |
Venkatakrishnan-Ramesh/Text_gen | [] | null | {
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"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/nickichlol/1667413921117/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; widt... |
CoffeeAddict93/gpt2-medium-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"no_repeat_ngram_size... | 14 | null | Access to model rxsong/bert-finetuned-ner_stake is restricted and you are not in the authorized list. Visit https://huggingface.co/rxsong/bert-finetuned-ner_stake to ask for access. |
CoffeeAddict93/gpt2-modest-proposal | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/chaddraven-nickichlol-saware7/1667415027467/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; marg... |
CogComp/roberta-temporal-predictor | [
"pytorch",
"roberta",
"fill-mask",
"arxiv:2202.00436",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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"no_repeat_ngra... | 14 | null | # Sorrentino Diffusion
Stable Diffusion model trained on images by the artists Andrea Sorrentino
<div style="display: flex; flex-direction: row; flex-wrap: wrap">
<img src="https://s3.amazonaws.com/moonup/production/uploads/1667417959158-6303f37c3926de1f7ec42d3e.png" width="256">
<img src="https://s3.amazonaws.com/... |
CohleM/mbert-nepali-tokenizer | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
---
# VQ Diffusion
* [Paper](https://arxiv.org/abs/2205.16007.pdf)
* [Original Repo](https://github.com/microsoft/VQ-Diffusion)
* **Authors**: Shuyang Gu, Dong Chen, et al.
```python
#!pip install diffusers[torch] transformers
import torch
from diffusers import VQDiffusionPipeline
pipeline = VQDi... |
Coldestadam/Breakout_Mentors_SpongeBob_Model | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: geevegeorge/customdbv3
metrics: []
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# cu... |
ComCom/gpt2-large | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- laion-2b
- imagenet-12k
---
# Model card for vit_huge_patch14_clip_336.laion2b_ft_in12k_in1k
A Vision Transformer (ViT) image classification model. Pretrained on LAION-2B image-text pairs using OpenCLIP. Fine-tuned... |
ComCom/gpt2-medium | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"model_type": "gpt2",
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 5 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- laion-2b
- imagenet-12k
---
# Model card for vit_large_patch14_clip_336.laion2b_ft_in12k_in1k
A Vision Transformer (ViT) image classification model. Pretrained on LAION-2B image-text pairs using OpenCLIP. Fine-tune... |
ComCom/gpt2 | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | 2022-11-02T19:00:22Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: smalldata-microsoft-deberta-base-eng-only-sentiment-single-finetuned-memes
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had acces... |
ComCom-Dev/gpt2-bible-test | [] | null | {
"architectures": null,
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-base-sroie
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# d... |
Cometasonmi451/Mine | [] | null | {
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- wit-400m
---
# Model card for vit_large_patch14_clip_224.openai_ft_in1k
A Vision Transformer (ViT) image classification model. Pretrained on WIT-400M image-text pairs by OpenAI using CLIP. Fine-tuned on ImageNet-1k... |
cometrain/neurotitle-rugpt3-small | [
"pytorch",
"gpt2",
"text-generation",
"ru",
"en",
"dataset:All-NeurIPS-Papers-Scraper",
"transformers",
"Cometrain AutoCode",
"Cometrain AlphaML",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 20 | null | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4... |
Connor-tech/bert_cn_finetuning | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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"max_length": null
},
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"min_length": null,
"no_rep... | 27 | null | ---
license: creativeml-openrail-m
---
waifu diffusion 1.3 base model with dreambooth training on images drawn by the artist "seero"
Can be used in StableDiffusion, including the extremely popular Web UI by Automatic1111, like any other model by placing the .CKPT file in the correct directory. Please consult the docu... |
Connorvr/TeachingGen | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
license: creativeml-openrail-m
---
waifu diffusion 1.3 base model with dreambooth training on images drawn by the artist "ozadomi"
Can be used in StableDiffusion, including the extremely popular Web UI by Automatic1111, like any other model by placing the .CKPT file in the correct directory. Please consult the do... |
ConstellationBoi/Oop | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
---
Hello! This is a 14,000 step trained model based on the famous Where's Waldo / Where's Wally art style. (I'm American so I named the style Waldo, if you're familiar with Wally instead, my apologies!)
The keyword to invoke the style is "Wheres Waldo style" and I've found it works best when you us... |
Contrastive-Tension/BERT-Base-CT-STSb | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-xls-r-300m-mn-demo
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove thi... |
Contrastive-Tension/BERT-Base-CT | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 16 | null | ---
license: mit
---
### Color Page on Stable Diffusion
This is the `<coloring-page>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ip... |
Contrastive-Tension/BERT-Large-CT-STSb | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: smalldata-distilbert-base-uncasede-eng-only-sentiment-single-finetuned-memes
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had acc... |
Cooker/cicero-similis | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: other
---
https://huggingface.co/dixipi9178/MyCoolModel/resolve/main/corneos7thHeavenMix_v2.safetensors
https://huggingface.co/dixipi9178/MyCoolModel/resolve/main/novelai%20f111%20sd1.4%20add%20difference%201.0.ckpt
https://huggingface.co/dixipi9178/MyCoolModel/resolve/main/Anything-V3.0-pruned-fp16.ck... |
CopymySkill/DialoGPT-medium-atakan | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- image-to-text
- image-captioning
widget:
- src: https://production-media.paperswithcode.com/datasets/MIMIC-CXR-0000002919-5d6519da_0miLqPx.jpg
example_title: chest-x-ray-1
license: mit
pinned: true
inference: true
---
|
CoveJH/ConBot | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... |
Coyotl/DialoGPT-test2-arthurmorgan | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: The-Fanta/distilbert-base-uncased-finetuned-cola
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this c... |
Craak/GJ0001 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- flax-sentence-embeddings/stackexchange_xml
- s2orc
- ms_marco
- wiki_atomic_edits
- snli
- multi_nli
- embedding-data/altlex
- embedding-data/simple-wiki
- embedd... |
Craig/paraphrase-MiniLM-L6-v2 | [
"pytorch",
"bert",
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1,026 | null | Access to model rxsong/bert-finetuned-promo is restricted and you are not in the authorized list. Visit https://huggingface.co/rxsong/bert-finetuned-promo to ask for access. |
CrayonShinchan/bart_fine_tune_test | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | Access to model rxsong/bert-finetuned-preven is restricted and you are not in the authorized list. Visit https://huggingface.co/rxsong/bert-finetuned-preven to ask for access. |
CrisLeaf/generador-de-historias-de-tolkien | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# alicekwak/TN-final-all-distilroberta-v1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks... |
Crispy/dialopt-small-kratos | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# alicekwak/TN-final-all-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks li... |
Crives/distilbert-base-uncased-finetuned-emotion | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:emotion",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 31 | null | ---
license: creativeml-openrail-m
---
waifu diffusion 1.3 base model with dreambooth training on images drawn by the artist "kagura_tohru"
Can be used in StableDiffusion, including the extremely popular Web UI by Automatic1111, like any other model by placing the .CKPT file in the correct directory. Please consult t... |
CrypticT1tan/DialoGPT-medium-harrypotter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# alicekwak/TN-final-multi-qa-mpnet-base-dot-v1
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and ... |
Culmenus/opus-mt-de-is-finetuned-de-to-is | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-base-payslips
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_35g65cc_1 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: pt-unicamp-handcrafted-puro
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_35g65cc_2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: creativeml-openrail-m
---
Artist 1: WLOP\
Patreon: https://www.patreon.com/wlop/posts
Artist 2: Nixeu\
Patreon: https://www.patreon.com/nixeu/posts
Artist 3: Cutesexyrobutts\
Patreon: https://www.patreon.com/cutesexyrobutts
## Basic explanation
Token words are what guide the AI to produce images simil... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_ekkicc | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- ko
tags:
- bert
- tokenizer only
license:
- mit
---
## 라이브러리 버전
- transformers: 4.23.1
- datasets: 2.6.1
- tokenizers: 0.13.1
[Bingsu/ko_BBPE_tokenizer_roberta](https://huggingface.co/Bingsu/ko_BBPE_tokenizer_roberta)에서 unicode normalizer를 `nfc`로, post-processor를 BertProcessing로 변경하고 토크나이저 클래... |
CuongLD/wav2vec2-large-xlsr-vietnamese | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:common_voice, infore_25h",
"arxiv:2006.11477",
"arxiv:2006.13979",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 8 | 2022-11-03T00:30:11Z | ---
language: en
tags:
- conversational
license: cc
---
# GPT-2
This model is based on a GPT-2 model which was fine-tuned on a Hugging Face dataset. It is intended largely as an illustrative example and is not intended to be used for any serious purpose. It's trained on a movie script for goodness' sake.
Disclaime... |
CurtisBowser/DialoGPT-medium-sora-three | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/swan_of_tuonela/1667438132238/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px;... |
D-Keqi/espnet_asr_train_asr_streaming_transformer_raw_en_bpe500_sp_valid.acc.ave | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: output_test
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# output_test
This model... |
D3xter1922/distilbert-base-uncased-finetuned-cola | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
language: [en, ko]
eos_token: "</s>"
widget:
- text: 혼자서 사전학습모델 만드는것은 너무 힘듭니다.</s>
---
# long-ke-t5 small
pretrained 1 epoch
Pretrained Long-T5 Model on Korean and English. See [Github](https://github.com/AIRC-KETI/long-ke-t5) for more details.
## How to use
```python
from transformers im... |
DCU-NLP/bert-base-irish-cased-v1 | [
"pytorch",
"tf",
"bert",
"fill-mask",
"transformers",
"generated_from_keras_callback",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1,244 | 2022-11-03T02:53:02Z | ---
tags:
- generated_from_trainer
model-index:
- name: Clinical-Longformer-SurgicalCardiothoracic
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Clinical-Lon... |
DJSammy/bert-base-swedish-uncased_BotXO-ai | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 1 | null | ---
tags:
- generated_from_trainer
model-index:
- name: gpt2-gpt2-mc-weight0.25-epoch2-new
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-gpt2-mc-weight0... |
DJStomp/TestingSalvoNET | [
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 1 | null | ---
tags:
- conversational
---
# nams DialoGPT Model |
DKpro000/DialoGPT-medium-harrypotter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
model-index:
- name: gpt2-gpt2-mc-weight0.25-epoch2-new-nosharing
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-gpt2-... |
DTAI-KULeuven/mbert-corona-tweets-belgium-topics | [
"pytorch",
"jax",
"bert",
"text-classification",
"multilingual",
"nl",
"fr",
"en",
"arxiv:2104.09947",
"transformers",
"Dutch",
"French",
"English",
"Tweets",
"Topic classification"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 167 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-1k
- wit-400m
- imagenet-12k
---
# Model card for vit_large_patch14_clip_224.openai_ft_in12k_in1k
A Vision Transformer (ViT) image classification model. Pretrained on WIT-400M image-text pairs by OpenAI using CLIP. Fine... |
DTAI-KULeuven/robbertje-1-gb-bort | [
"pytorch",
"roberta",
"fill-mask",
"nl",
"dataset:oscar",
"dataset:oscar (NL)",
"dataset:dbrd",
"dataset:lassy-ud",
"dataset:europarl-mono",
"dataset:conll2002",
"arxiv:2101.05716",
"transformers",
"Dutch",
"Flemish",
"RoBERTa",
"RobBERT",
"RobBERTje",
"license:mit",
"autotrain_c... | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 6 | null | ---
tags:
- image-classification
- timm
library_name: timm
license: apache-2.0
datasets:
- imagenet-12k
- wit-400m
---
# Model card for vit_large_patch14_clip_224.openai_ft_in12k
A Vision Transformer (ViT) image classification model. Pretrained on WIT-400M image-text pairs by OpenAI using CLIP. Fine-tuned on ImageNet-... |
DTAI-KULeuven/robbertje-1-gb-non-shuffled | [
"pytorch",
"roberta",
"fill-mask",
"nl",
"dataset:oscar",
"dataset:dbrd",
"dataset:lassy-ud",
"dataset:europarl-mono",
"dataset:conll2002",
"arxiv:2101.05716",
"transformers",
"Dutch",
"Flemish",
"RoBERTa",
"RobBERT",
"RobBERTje",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 53 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
... |
alexandrainst/da-hatespeech-classification-base | [
"pytorch",
"tf",
"safetensors",
"bert",
"text-classification",
"da",
"transformers",
"license:cc-by-sa-4.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 866 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... |
alexandrainst/da-ner-base | [
"pytorch",
"tf",
"bert",
"token-classification",
"da",
"dataset:dane",
"transformers",
"license:cc-by-sa-4.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 78 | null | ---
language:
- zh
license: apache-2.0
tags:
- roberta
- NLU
- NLI
- Chinese
inference: true
widget:
- text: "鲸鱼是哺乳动物，所有哺乳动物都是恒温动物[SEP]鲸鱼也是恒温动物"
- text: "葡萄树是阔叶植物，所有阔叶植物都不会落叶[SEP]葡萄树是落叶植物"
- text: "玉米价格持续上涨，饲料主要的来源是玉米[SEP]饲料价格可能会上涨"
---
# Erlangshen-Roberta-330M-Causal-Chinese
- Github: [Fengshenbang-LM](https:... |
DaWang/demo | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: zh
---
## BioStd Model Hubs
### [模型仓库](https://huggingface.co/chaleris/biostd_hub/tree/main/models)
| name | s_dim | c_dim | p_dim | e_dim | total_dim | 兼容版本 |
| ----------------------------------- | ----- | ----- | ----- | ----- | --------- | -------- |
| `v1.3.0/v1.3.0-... |
Dablio/Dablio | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... |
Daltcamalea01/Camaleaodalt | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: zero-shot-classification
widget:
- text: "Jens Peter Hansen kommer fra Danmark"
--- |
DarkestSky/distilbert-base-uncased-finetuned-ner | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ## Randeng-DAVAE-1.2B-General-Chinese
- Github: [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM/tree/main/fengshen/models/DAVAE)
- Docs: [Fengshenbang-Docs](https://fengshenbang-doc.readthedocs.io/zh/latest/docs/%E7%87%83%E7%81%AF%E7%B3%BB%E5%88%97/Randeng-DAVAE-1.2B-General-Chinese.html)
## 简介 Brief I... |
Darkrider/covidbert_medmarco | [
"pytorch",
"jax",
"bert",
"text-classification",
"arxiv:2010.05987",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 35 | null | ---
license: apache-2.0
tags:
- vision
- simmim
datasets:
- imagenet-1k
inference: false
---
# Swin Transformer (base-sized model)
Swin Transformer model pre-trained on ImageNet-1k using the SimMIM objective at resolution 192x192. It was introduced in the paper [SimMIM: A Simple Framework for Masked Image Modeling](... |
DataikuNLP/TinyBERT_General_4L_312D | [
"pytorch",
"jax",
"bert",
"arxiv:1909.10351",
"transformers"
] | null | {
"architectures": null,
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_bea... | 74 | null | ---
license: apache-2.0
tags:
- vision
- simmim
datasets:
- imagenet-1k
inference: false
---
# Swin Transformer (large-sized model)
Swin Transformer model pre-trained on ImageNet-1k using the SimMIM objective at resolution 192x192. It was introduced in the paper [SimMIM: A Simple Framework for Masked Image Modeling]... |
DavidAMcIntosh/DialoGPT-small-rick | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
language:
- lb
- en
metrics:
- bleu
---
Luxembourgish to English model, using knowledge distillation
|
Davlan/bert-base-multilingual-cased-finetuned-amharic | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 109 | 2022-11-03T10:34:38Z | ---
license: mit
---
### Franz Unterberger on Stable Diffusion
This is the `<franz-unterberger>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_i... |
Davlan/bert-base-multilingual-cased-finetuned-luganda | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 16 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: t5-small-science-papers
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_pa... |
Davlan/bert-base-multilingual-cased-finetuned-yoruba | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 21 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: ViT_exp_1
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9732142686843872
---
# ViT_exp_1
Autogenerate... |
Davlan/bert-base-multilingual-cased-masakhaner | [
"pytorch",
"tf",
"bert",
"token-classification",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 88 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: smalldata-microsoft-deberta-base-mnli-eng-only-sentiment-single-finetuned-memes
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access ... |
Davlan/bert-base-multilingual-cased-ner-hrl | [
"pytorch",
"tf",
"bert",
"token-classification",
"transformers",
"autotrain_compatible",
"has_space"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 269,898 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete i... |
Davlan/byt5-base-eng-yor-mt | [
"pytorch",
"t5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 11 | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: twitter-data-pysentimiento-robertuito-sentiment-finetuned-memes
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... |
Davlan/mT5_base_yoruba_adr | [
"pytorch",
"mt5",
"text2text-generation",
"arxiv:2003.10564",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-or-colab
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then rem... |
Davlan/mbart50-large-eng-yor-mt | [
"pytorch",
"mbart",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 5 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# pritamdeka/BioBERT-mnli-snli-scinli-scitail-mednli-stsb
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector s... |
Davlan/mt5-small-en-pcm | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 9 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# pritamdeka/PubMedBERT-mnli-snli-scinli-scitail-mednli-stsb
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vecto... |
Davlan/mt5_base_yor_eng_mt | [
"pytorch",
"mt5",
"text2text-generation",
"arxiv:2103.08647",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 8 | null | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- MS-Go/autotrain-data-hjuihu
co2_eq_emissions:
emissions: 49.671043265609676
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1974565969
- CO2 Emissions (in grams): 49.6710
## Validat... |
Davlan/naija-twitter-sentiment-afriberta-large | [
"pytorch",
"tf",
"xlm-roberta",
"text-classification",
"arxiv:2201.08277",
"transformers",
"has_space"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 61 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
model-index:
- name: distilbert-base-uncased-finetuned-imdb
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove ... |
Davlan/xlm-roberta-base-finetuned-chichewa | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 5 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# pritamdeka/SapBERT-mnli-snli-scinli-scitail-mednli-stsb
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector s... |
Davlan/xlm-roberta-base-finetuned-kinyarwanda | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 61 | null | ---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: huggan/smithsonian_butterflies_subset
metrics: []
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this com... |
Davlan/xlm-roberta-base-finetuned-luganda | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 11 | 2022-11-03T13:05:08Z | ---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: huggan/smithsonian_butterflies_subset
metrics: []
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this com... |
Davlan/xlm-roberta-base-finetuned-luo | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remov... |
Davlan/xlm-roberta-base-finetuned-wolof | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 3 | null | ---
license: apache-2.0
description: wav2vec2 based model for malayalam-english code-switched speech
language:
- ml
- en
tags:
- automatic-speech-recognition
- malayalam
- ml_en
- code-switching
datasets:
- erose/code_switching-ml-en
model-index:
- name: wav2vec2 ml_en
results:
- task:
name: Automatic Speech ... |
Davlan/xlm-roberta-base-finetuned-yoruba | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 29 | null | ---
license: apache-2.0
---
```python
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-torch")
```
|
Davlan/xlm-roberta-base-finetuned-zulu | [
"pytorch",
"xlm-roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"XLMRobertaForMaskedLM"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-music-genres-small
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then r... |
Davlan/xlm-roberta-base-masakhaner | [
"pytorch",
"xlm-roberta",
"token-classification",
"arxiv:2103.11811",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 3 | null | ---
pipeline_tag: sentence-similarity
language:
- 'pt'
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
datasets:
- 'unicamp-dl/mmarco'
---
# mpjan/msmarco-distilbert-base-tas-b-mmarco-pt-100k
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences ... |
Davlan/xlm-roberta-base-wikiann-ner | [
"pytorch",
"tf",
"xlm-roberta",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 235 | null | ---
license: mit
datasets:
- Wannita/PyCoder
- Wannita/PyCoder-Type
metrics:
- accuracy
- bleu
- meteor
- exact_match
- rouge
library_name: transformers
pipeline_tag: text-generation
tags:
- code
- code completion
---
# PyCoder
This repository contains the model for the paper [Syntax-Aware On-the-Fly Code Completion](... |
Dawit/DialogGPT-small-ironman | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
---
This was trained with Pepe Larraz's work. He is **not** affiliated with this. The correct token is comicmay artsyle.
**Generated by this model:**
![Samples](https://huggingfac... |
Daymarebait/Discord_BOT_RICK | [
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: imdb-distilbert-base-cased
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# imdb-di... |
Dazai/Ok | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- flair
- token-classification
- sequence-tagger-model
---
### Demo: How to use in Flair
Requires:
- **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
```python
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("GuiGel/meddoc... |
DeadBeast/marathi-roberta-base | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- en
license: creativeml-openrail-m
thumbnail: "https://huggingface.co/Guizmus/Tardisfusion/resolve/main/showcase.jpg"
tags:
- stable-diffusion
- text-to-image
- image-to-image
inference: true
---
# TARDISfusion
<p>
<img src="https://huggingface.co/Guizmus/Tardisfusion/raw/main/showcase.jpg"/><br/>
Thi... |
DeadBeast/mbert-base-cased-finetuned-bengali-fakenews | [
"pytorch",
"bert",
"text-classification",
"bengali",
"dataset:BanFakeNews",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 37 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny-bert-sst2-distilled
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- name: Accuracy... |
DeadBeast/roberta-base-pretrained-mr | [
"jax",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 6 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: pegasus-base-qag-bg-finetuned-grammar-bg
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# p... |
Dean/summarsiation | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/cosm1cgrandma/1667487071319/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; w... |
DecafNosebleed/DialoGPT-small-ScaraBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 15 | null | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- MS-Go/autotrain-data-bart_normaldata
co2_eq_emissions:
emissions: 41.152874017879256
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 1976866012
- CO2 Emissions (in grams): 41.1529
#... |
Declan/Breitbart_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-mlm-feedback
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-mlm-feedback... |
Declan/Breitbart_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/cosm1cgrandma-raptv/1667487735762/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: ... |
Declan/Breitbart_model_v6 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
---
# DMVC2
This is an own SD trainee with an 2000s videogame illustrations as a style.
If you wanna test it, you can put this word on the prompt: DMVC2 . Sometimes you must put before things like 'an illustration of'
If you enjoy my work, p... |
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