Instructions to use flavienbwk/example-dummy-evaluation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flavienbwk/example-dummy-evaluation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("flavienbwk/example-dummy-evaluation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
flavienbwk commited on
Commit ·
59bf28c
1
Parent(s): 32bdc50
Now using dill file
Browse files- example-dummy-evaluation.dill +0 -0
- example-dummy-evaluation.pkl +0 -3
- train.py +4 -4
example-dummy-evaluation.dill
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Binary file (3.9 kB). View file
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example-dummy-evaluation.pkl
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@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:db681019f6fde303497efa1d273f12002c2ae41ce973615e81b3f1d246a368e7
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size 1912
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train.py
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@@ -1,4 +1,4 @@
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import
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from transformers import PreTrainedModel, PretrainedConfig
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class CountAModel(PreTrainedModel):
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@@ -23,9 +23,9 @@ sentence = "This is a sample sentence with a few 'a's."
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count_a = model(sentence)
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print(f"The sentence contains {count_a} letter(s) 'a'.")
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-
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# Save the model in the current directory
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model.save_pretrained(".")
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with open('example-dummy-evaluation.
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print("Model saved successfully.")
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import dill
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from transformers import PreTrainedModel, PretrainedConfig
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class CountAModel(PreTrainedModel):
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count_a = model(sentence)
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print(f"The sentence contains {count_a} letter(s) 'a'.")
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# Save the model in the current directory
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model.save_pretrained(".")
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with open('example-dummy-evaluation.dill', 'wb') as f:
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dill.dump(model, f)
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dill.dump(CountAModel, f)
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print("Model saved successfully.")
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