Add files using upload-large-folder tool
Browse files- README.md +10 -3
- safety_checker/config.json +1 -1
- smash_config.json +3 -0
- text_encoder/config.json +1 -1
README.md
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library_name: diffusers
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tags:
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- pruna-ai
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---
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# Model Card for PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed
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```python
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from pruna import PrunaModel
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loaded_model = PrunaModel.
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"PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed"
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)
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```
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-
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## Smash Configuration
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"cacher": null,
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"compiler": null,
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"factorizer": null,
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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"device": "cpu",
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"save_fns": [],
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"load_fns": [
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"diffusers"
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"factorizer": null,
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"pruner": null,
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"quantizer": null,
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"cacher": null,
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"compiler": null,
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"batcher": null
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[](https://github.com/PrunaAI)
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[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
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[](https://discord.com/invite/rskEr4BZJx)
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-
[](https://www.reddit.com/r/PrunaAI/)
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library_name: diffusers
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tags:
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- pruna-ai
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- safetensors
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---
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# Model Card for PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed
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```python
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from pruna import PrunaModel
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loaded_model = PrunaModel.from_pretrained(
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"PrunaAI/test-save-tiny-stable-diffusion-pipe-smashed"
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)
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# we can then run inference using the methods supported by the base model
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```
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For inference, you can use the inference methods of the original model like shown in [the original model card](https://huggingface.co/hf-internal-testing/tiny-stable-diffusion-pipe?library=diffusers).
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Alternatively, you can visit [the Pruna documentation](https://docs.pruna.ai/en/stable/) for more information.
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## Smash Configuration
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"cacher": null,
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"compiler": null,
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"factorizer": null,
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"kernel": null,
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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"device": "cpu",
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"device_map": null,
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"save_fns": [],
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"load_fns": [
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"diffusers"
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"factorizer": null,
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"pruner": null,
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"quantizer": null,
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"kernel": null,
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"cacher": null,
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"compiler": null,
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"batcher": null
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[](https://github.com/PrunaAI)
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[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
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[](https://discord.com/invite/rskEr4BZJx)
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[](https://www.reddit.com/r/PrunaAI/)
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safety_checker/config.json
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"vocab_size": 99
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},
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"torch_dtype": "float32",
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"transformers_version": "4.52.
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"vision_config": {
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"attention_dropout": 0.1,
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"dropout": 0.1,
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"vocab_size": 99
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},
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"torch_dtype": "float32",
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"transformers_version": "4.52.3",
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"vision_config": {
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"attention_dropout": 0.1,
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"dropout": 0.1,
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smash_config.json
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"cacher": null,
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"compiler": null,
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"factorizer": null,
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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"device": "cpu",
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"save_fns": [],
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"load_fns": [
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"diffusers"
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"factorizer": null,
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"pruner": null,
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"quantizer": null,
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"cacher": null,
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"compiler": null,
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"batcher": null
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"cacher": null,
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"compiler": null,
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"factorizer": null,
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"kernel": null,
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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"device": "cpu",
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"device_map": null,
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"save_fns": [],
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"load_fns": [
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"diffusers"
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"factorizer": null,
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"pruner": null,
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"quantizer": null,
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"kernel": null,
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"cacher": null,
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"compiler": null,
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"batcher": null
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text_encoder/config.json
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"pad_token_id": 1,
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"projection_dim": 512,
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"torch_dtype": "float32",
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"transformers_version": "4.52.
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"vocab_size": 1000
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}
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"pad_token_id": 1,
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"projection_dim": 512,
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"torch_dtype": "float32",
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"transformers_version": "4.52.3",
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"vocab_size": 1000
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}
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