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Create README.md

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+ Small dummy deberta-v3-type Model useable for Unit/Integration tests. Suitable for CPU only machines, see [H2O LLM Studio](https://github.com/h2oai/h2o-llmstudio/blob/main/tests/integration/test_integration.py) for an example integration test.
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+
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+ Model was created as follows:
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+ ```python
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+ from transformers import AutoConfig, AutoTokenizer, AutoModelForSequenceClassification
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+
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+ repo_name = "MaxJeblick/reward-model-deberta-v3-unit-test"
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+ model_name = "OpenAssistant/reward-model-deberta-v3-large-v2"
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+ config = AutoConfig.from_pretrained(model_name)
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+
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+ config.hidden_size = 12
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+ config.intermediate_size = 24
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+ config.num_attention_heads = 2
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+ config.num_hidden_layers = 2
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+ config.pooler_hidden_size = 12
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+
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+ model = AutoModelForSequenceClassification.from_config(config)
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+ print(model.num_parameters()) # 1_546_129
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+
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+
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+ model.push_to_hub(repo_name, private=False)
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+ tokenizer.push_to_hub(repo_name, private=False)
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+ config.push_to_hub(repo_name, private=False)
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+ ```