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--- |
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language: |
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- en |
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datasets: |
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- kyujinpy/Open-platypus-Commercial |
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library_name: transformers |
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pipeline_tag: text-generation |
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license: mit |
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--- |
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# **phi-2-test** |
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## Model Details |
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**Model Developers** |
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- field2437 |
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**Base Model** |
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- microsoft/phi-2(https://huggingface.co/microsoft/phi-2) |
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**Training Dataset** |
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- kyujinpy/Open-platypus-Commercial(https://huggingface.co/datasets/kyujinpy/Open-platypus-Commercial) |
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--- |
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# Model comparisons1 |
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--- |
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# Model comparisons2 |
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> AI-Harness evaluation; [link](https://github.com/EleutherAI/lm-evaluation-harness) |
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| Model | Copa | HellaSwag | BoolQ | MMLU | |
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| --- | --- | --- | --- | --- | |
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| | 0-shot | 0-shot | 0-shot | 0-shot | |
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| **field2437/phi-2-test** | 0.8900 | NaN | 0.5573 | NaN | 0.8260 | NaN | 0.5513 | NaN | |
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--- |
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# Sample Code |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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torch.set_default_device("cuda") |
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model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2", torch_dtype="auto", trust_remote_code=True) |
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tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2", trust_remote_code=True) |
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inputs = tokenizer('''def print_prime(n): |
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""" |
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Print all primes between 1 and n |
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"""''', return_tensors="pt", return_attention_mask=False) |
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outputs = model.generate(**inputs, max_length=200) |
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text = tokenizer.batch_decode(outputs)[0] |
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print(text) |
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``` |
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--- |
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