Add files using upload-large-folder tool
Browse files- README.md +5 -3
- config.json +1 -1
- generation_config.json +1 -1
- smash_config.json +2 -0
README.md
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- pruna-ai
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---
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# Model Card for PrunaAI/test-tiny-random-llama4-smashed
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This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.
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pip install pruna
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```
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You can [use the transformers library to load the model](https://huggingface.co/PrunaAI/test-tiny-random-llama4-smashed?library=transformers) but this might not include all optimizations by default.
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To ensure that all optimizations are applied, use the pruna library to load the model using the following code:
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from pruna import PrunaModel
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loaded_model = PrunaModel.from_hub(
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"PrunaAI/test-tiny-random-llama4-smashed"
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)
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```
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"batcher": null,
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"cacher": null,
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"compiler": null,
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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"transformers"
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],
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"reapply_after_load": {
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"pruner": null,
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"quantizer": null,
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"cacher": null,
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- pruna-ai
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---
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+
# Model Card for PrunaAI/test-load-tiny-random-llama4-smashed
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This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.
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pip install pruna
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```
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+
You can [use the transformers library to load the model](https://huggingface.co/PrunaAI/test-load-tiny-random-llama4-smashed?library=transformers) but this might not include all optimizations by default.
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To ensure that all optimizations are applied, use the pruna library to load the model using the following code:
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from pruna import PrunaModel
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loaded_model = PrunaModel.from_hub(
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"PrunaAI/test-load-tiny-random-llama4-smashed"
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)
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```
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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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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"transformers"
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],
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"reapply_after_load": {
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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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config.json
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"router_jitter_noise": 0.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"use_qk_norm": true,
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"vocab_size": 202048
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"router_jitter_noise": 0.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.52.4",
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"use_cache": true,
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"use_qk_norm": true,
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"vocab_size": 202048
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generation_config.json
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200008
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],
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"pad_token_id": 200018,
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"transformers_version": "4.
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}
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200008
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],
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"pad_token_id": 200018,
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"transformers_version": "4.52.4"
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}
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smash_config.json
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"batcher": null,
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"cacher": null,
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"compiler": null,
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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"transformers"
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],
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"reapply_after_load": {
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"pruner": null,
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"quantizer": null,
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"cacher": 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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"pruner": null,
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"quantizer": null,
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"batch_size": 1,
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"transformers"
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],
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"reapply_after_load": {
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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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