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Model: UnfilteredAI/Promt-generator
Source: Original Platform

.gitattributes

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.gitignore

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+checkpoint-*/

README.md

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+---
+license: mit
+---
+
+## Model Card: UnfilteredAI/Promt-generator
+
+### Model Overview
+The **UnfilteredAI/Promt-generator** is a text generation model designed specifically for creating prompts for text-to-image models. It leverages **PyTorch** and **safetensors** for optimized performance and storage, ensuring that it can be easily deployed and scaled for prompt generation tasks.
+
+
+### Intended Use
+This model is primarily intended for:
+- **Prompt generation** for text-to-image models.
+- Creative AI applications where generating high-quality, diverse image descriptions is critical.
+- Supporting AI artists and developers working on generative art projects.
+
+### How to Use
+To generate prompts using this model, follow these steps:
+
+1. Load the model in your PyTorch environment.
+2. Input your desired parameters for the prompt generation task.
+3. The model will return text descriptions based on the input, which can then be used with text-to-image models.
+
+**Example Code:**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("UnfilteredAI/Promt-generator")
+model = AutoModelForCausalLM.from_pretrained("UnfilteredAI/Promt-generator")
+
+prompt = "a red car"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs)
+generated_prompt = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(generated_prompt)
+```

config.json

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+{
+  "_name_or_path": "bigscience/bloom-560m",
+  "apply_residual_connection_post_layernorm": false,
+  "architectures": [
+    "BloomForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "attention_softmax_in_fp32": true,
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+  "bos_token_id": 1,
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+  "hidden_dropout": 0.0,
+  "hidden_size": 1024,
+  "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,
+  "seq_length": 2048,
+  "skip_bias_add": true,
+  "skip_bias_add_qkv": false,
+  "slow_but_exact": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.22.1",
+  "unk_token_id": 0,
+  "use_cache": false,
+  "vocab_size": 250880
+}

model.safetensors

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pytorch_model.bin

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special_tokens_map.json

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+  "bos_token": "<s>",
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+  "pad_token": "<pad>",
+  "unk_token": "<unk>"
+}

tokenizer.json

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tokenizer_config.json

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+  "name_or_path": "bigscience/bloom-560m",
+  "pad_token": "<pad>",
+  "padding_side": "left",
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+  "tokenizer_class": "BloomTokenizer",
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+}

training_args.bin

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