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README.md

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+---
+license: other
+language:
+- en
+pipeline_tag: text-generation
+inference: false
+tags:
+- transformers
+- gguf
+- imatrix
+- Asclepius-Llama2-13B
+---
+Quantizations of https://huggingface.co/starmpcc/Asclepius-Llama2-13B
+
+
+### Inference Clients/UIs
+* [llama.cpp](https://github.com/ggerganov/llama.cpp)
+* [JanAI](https://github.com/janhq/jan)
+* [KoboldCPP](https://github.com/LostRuins/koboldcpp)
+* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
+* [ollama](https://github.com/ollama/ollama)
+* [GPT4All](https://github.com/nomic-ai/gpt4all)
+
+---
+
+# From original readme
+
+## How to Get Started with the Model
+
+```python
+prompt = """You are an intelligent clinical languge model.
+Below is a snippet of patient's discharge summary and a following instruction from healthcare professional.
+Write a response that appropriately completes the instruction.
+The response should provide the accurate answer to the instruction, while being concise.
+
+[Discharge Summary Begin]
+{note}
+[Discharge Summary End]
+
+[Instruction Begin]
+{question}
+[Instruction End] 
+"""
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("starmpcc/Asclepius-Llama2-13B", use_fast=False)
+model = AutoModelForCausalLM.from_pretrained("starmpcc/Asclepius-Llama13-7B")
+
+note = "This is a sample note"
+question = "What is the diagnosis?"
+
+model_input = prompt.format(note=note, question=question)
+input_ids = tokenizer(model_input, return_tensors="pt").input_ids
+output = model.generate(input_ids)
+print(tokenizer.decode(output[0]))
+```