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Quantization made by Richard Erkhov. |
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[Github](https://github.com/RichardErkhov) |
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[Discord](https://discord.gg/pvy7H8DZMG) |
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[Request more models](https://github.com/RichardErkhov/quant_request) |
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phi-2 - bnb 4bits |
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- Model creator: https://huggingface.co/susnato/ |
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- Original model: https://huggingface.co/susnato/phi-2/ |
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Original model description: |
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--- |
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license: mit |
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license_name: microsoft-research-license |
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license_link: LICENSE |
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--- |
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**DISCLAIMER**: I don't own the weights to this model, this is a property of Microsoft and taken from their official repository : [microsoft/phi-2](https://huggingface.co/microsoft/phi-2). |
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The sole purpose of this repository is to use this model through the `transformers` API or to load and use the model using the HuggingFace `transformers` library. |
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# Usage |
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First make sure you have the latest version of the `transformers` installed. |
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``` |
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pip uninstall -y transformers && pip install git+https://github.com/huggingface/transformers |
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``` |
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Then use the transformers library to load the model from the library itself |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("susnato/phi-2") |
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tokenizer = AutoTokenizer.from_pretrained("susnato/phi-2") |
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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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