Update README.md

Initial commit with just notes

README.md

@@ -1,3 +1,57 @@
 ---
 license: llama2
 ---
+Quick notes--what I did to get to this point
+
+```
+from optimum.neuron import NeuronModelForCausalLM
+from transformers import AutoTokenizer
+model_id = "TencentARC/LLaMA-Pro-8B"
+compiler_args = {"num_cores": 2, "auto_cast_type": "fp16"}
+input_shapes = {"sequence_length": 2048, "batch_size": 2 }
+llm = NeuronModelForCausalLM.from_pretrained(model_id, export=True, **input_shapes, **compiler_args)
+save_directory = "Tencent_neuron"
+
+llm.save_pretrained(save_directory)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+tokenizer.save_pretrained(save_directory)
+
+quit()
+```
+
+```
+from optimum.neuron import pipeline
+
+# Load pipeline from Hugging Face repository
+save_directory = "Tencent_neuron"
+
+pipe = pipeline("text-generation", save_directory)
+
+# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
+messages = [
+    {"role": "user", "content": "What is 2+2?"},
+]
+prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+# Run generation
+outputs = pipe(prompt, max_new_tokens=2048, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+
+```
+```
+from huggingface_hub import login
+from huggingface_hub import HfApi
+api = HfApi()
+login()
+
+
+save_directory = "Tencent_neuron"
+
+api.upload_folder(
+    folder_path=save_directory,
+    repo_id="jburtoft/TencentARC-LLaMA-Pro-8B-Neuron",
+    repo_type="model",
+    multi_commits=True,
+    multi_commits_verbose=True,
+)
+```