Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) phi-2 - bnb 4bits - Model creator: https://huggingface.co/susnato/ - Original model: https://huggingface.co/susnato/phi-2/ Original model description: --- license: mit license_name: microsoft-research-license license_link: LICENSE --- **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). 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. # Usage First make sure you have the latest version of the `transformers` installed. ``` pip uninstall -y transformers && pip install git+https://github.com/huggingface/transformers ``` Then use the transformers library to load the model from the library itself ```python from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained("susnato/phi-2") tokenizer = AutoTokenizer.from_pretrained("susnato/phi-2") inputs = tokenizer('''def print_prime(n): """ Print all primes between 1 and n """''', return_tensors="pt", return_attention_mask=False) outputs = model.generate(**inputs, max_length=200) text = tokenizer.batch_decode(outputs)[0] print(text) ```