Update README.md

README.md

@@ -1,3 +1,33 @@
 ---
 license: bsd-3-clause
+metrics:
+- code_eval
+pipeline_tag: text-generation
+tags:
+- code
 ---
+# Model Card for instruct-codegen-16B
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+Instruct-codegen-16B is an instruction following codegen model based on [Salesforce codegen-16B-multi](https://huggingface.co/Salesforce/codegen-16B-multi) , finetuned on a dataset of 250k instruction-following samples in the alpaca format.
+
+The data was not generated using any commercial LLM api.
+
+The model achieves a new SoTA result of 36.1% pass@1 on the HumanEval benchmark.
+
+## Generation
+
+```python
+# pip install -q transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+checkpoint = "sahil2801/instruct-codegen-16B"
+device = "cuda"
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+model = AutoModelForCausalLM.from_pretrained(checkpoint).half().to(device)
+instruction = "Write a function to scrape hacker news."
+prompt = f"Below is an instruction that describes a task.\n Write a response that appropriately completes the request.\n\n ### Instruction:\n{instruction}\n\n### Response:"
+inputs = tokenizer(prompt, return_tensors="pt").to(device)
+outputs = model.generate(**inputs,temperature=0.3,do_sample=True)
+print(tokenizer.decode(outputs[0],skip_special_tokens=True))
+```