Instructions to use akshan-main/tiny-ltx-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akshan-main/tiny-ltx-modular-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("akshan-main/tiny-ltx-modular-pipe", 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
Fix text encoder vocab_size to match T5TokenizerFast (32100)
Browse files
text_encoder/config.json
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],
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"classifier_dropout": 0.0,
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"d_ff": 64,
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"d_kv":
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"d_model": 32,
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"dense_act_fn": "relu",
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"dropout_rate": 0.1,
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"dtype": "float32",
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"relative_attention_num_buckets": 32,
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"transformers_version": "4.57.3",
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"use_cache": false,
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"vocab_size":
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}
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],
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"classifier_dropout": 0.0,
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"d_ff": 64,
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"d_kv": 8,
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"d_model": 32,
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"decoder_start_token_id": 0,
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"dense_act_fn": "relu",
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"dropout_rate": 0.1,
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"dtype": "float32",
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"relative_attention_num_buckets": 32,
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"transformers_version": "4.57.3",
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"use_cache": false,
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"vocab_size": 32100
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}
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text_encoder/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:d2a37f231053149206b880238f4cdd65fade101a87112d2cf3a967b2dc4cf0a5
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size 4143672
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