Instructions to use schrum2/MarioDiffusion-MLM-regular0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use schrum2/MarioDiffusion-MLM-regular0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("schrum2/MarioDiffusion-MLM-regular0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
changed import
Browse files
text_encoder/text_model.py
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@@ -6,7 +6,7 @@ import math
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import os
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import json
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from safetensors.torch import save_file, load_file
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from tokenizer import Tokenizer
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def get_embeddings(batch_size, tokenizer, text_encoder, captions=None, neg_captions=None, device='cpu'):
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max_length = text_encoder.max_seq_length
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import os
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import json
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from safetensors.torch import save_file, load_file
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from tokenizer.tokenizer import Tokenizer
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def get_embeddings(batch_size, tokenizer, text_encoder, captions=None, neg_captions=None, device='cpu'):
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max_length = text_encoder.max_seq_length
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