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Model: pai/pai-bloom-1b1-text2prompt-sd
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+widget:
+  - text: "Instruction: Give a simple description of the image to generate a drawing prompt.\nInput: 1 girl\nOutput:"
+tags:
+- pytorch
+- transformers
+- text-generation
+---
+
+# BeautifulPrompt
+
+## 简介 Brief Introduction
+
+我们开源了一个自动Prompt生成模型，您可以直接输入一个极其简单的Prompt，就可以得到经过语言模型优化过的Prompt，帮助您更简单地生成高颜值图像。
+
+We release an automatic Prompt generation model, you can directly enter an extremely simple Prompt and get a Prompt optimized by the language model to help you generate more beautiful images simply.
+
+* Github: [EasyNLP](https://github.com/alibaba/EasyNLP)
+
+## 使用 Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained('alibaba-pai/pai-bloom-1b1-text2prompt-sd')
+model = AutoModelForCausalLM.from_pretrained('alibaba-pai/pai-bloom-1b1-text2prompt-sd').eval().cuda()
+
+raw_prompt = '1 girl'
+input = f'Instruction: Give a simple description of the image to generate a drawing prompt.\nInput: {raw_prompt}\nOutput:'
+input_ids = tokenizer.encode(input, return_tensors='pt').cuda()
+
+outputs = model.generate(
+    input_ids,
+    max_length=384,
+    do_sample=True,
+    temperature=1.0,
+    top_k=50,
+    top_p=0.95,
+    repetition_penalty=1.2,
+    num_return_sequences=5)
+
+prompts = tokenizer.batch_decode(outputs[:, input_ids.size(1):], skip_special_tokens=True)
+prompts = [p.strip() for p in prompts]
+print(prompts)
+```
+
+## 作品展示 Gallery
+
+<style>
+table th:first-of-type {
+    width: 50%;
+}
+table th:nth-of-type(2) {
+    width: 50%;
+}
+</style>
+
+| Original | BeautifulPrompt |
+| ---------------------------------------- | ---------------------------------- |
+| prompt: taylor swift, country, golden, fearless,wavehair | prompt: portrait of taylor swift as a beautiful woman, long hair, country, golden ratio, intricate, symmetrical, cinematic lighting, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration |
+| ![](example1.png)                        | ![](example2.png)                  |
+
+
+| Original | BeautifulPrompt |
+| ---------------------------------------- | ---------------------------------- |
+| prompt: A majestic sailing ship | prompt: a massive sailing ship, epic, cinematic,    artstation, greg rutkowski, james gurney, sparth |
+| ![](example3.png)                        | ![](example4.png)                  |
+
+
+
+## 使用须知 Notice for Use
+
+使用上述模型需遵守[AIGC模型开源特别条款](https://terms.alicdn.com/legal-agreement/terms/common_platform_service/20230505180457947/20230505180457947.html)。
+
+If you want to use this model, please read this [document](https://terms.alicdn.com/legal-agreement/terms/common_platform_service/20230505180457947/20230505180457947.html) carefully and abide by the terms.
+
+## Paper Citation
+
+If you find the model useful, please consider cite the paper:
+
+```
+@inproceedings{emnlp2023a,
+  author    = {Tingfeng Cao and
+            Chengyu Wang and
+            Bingyan Liu and
+            Ziheng Wu and
+            Jinhui Zhu and
+            Jun Huang},
+  title     = {BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis},
+  booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track},
+  pages     = {1--11},
+  year      = {2023}
+}
+```
+
+
+

config.json

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+{
+  "_name_or_path": "alibaba-pai/pai-bloom-1b1-text2prompt-sd",
+  "apply_residual_connection_post_layernorm": false,
+  "architectures": [
+    "BloomForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "attention_softmax_in_fp32": true,
+  "bias_dropout_fusion": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_dropout": 0.0,
+  "hidden_size": 1536,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "masked_softmax_fusion": true,
+  "model_type": "bloom",
+  "n_head": 16,
+  "n_inner": null,
+  "n_layer": 24,
+  "offset_alibi": 100,
+  "pad_token_id": 3,
+  "pretraining_tp": 1,
+  "skip_bias_add": true,
+  "skip_bias_add_qkv": false,
+  "slow_but_exact": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.27.4",
+  "unk_token_id": 0,
+  "use_cache": true,
+  "vocab_size": 250880
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 3,
+  "transformers_version": "4.29.2"
+}

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special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "pad_token": "</s>",
+  "sep_token": "<sep>",
+  "unk_token": "<unk>"
+}

tokenizer.json

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "padding_side": "left",
+  "tokenizer_class": "BloomTokenizer",
+  "unk_token": "<unk>"
+}