Update README.md

README.md

@@ -51,10 +51,37 @@ pipeline_tag: text-generation
 {Assistant}
 ```
 
+## Usage
+
+- Tested on A100 80GB
+- Our model can handle up to 10k input tokens, thanks to the `rope_scaling` option
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+
+tokenizer = AutoTokenizer.from_pretrained("upstage/llama-30b-instruct")
+model = AutoModelForCausalLM.from_pretrained(
+    "upstage/llama-30b-instruct",
+    device_map="auto",
+    torch_dtype=torch.float16,
+    load_in_8bit=True,
+    rope_scaling={"type": "dynamic", "factor": 2} # allows handling of longer inputs
+)
+
+prompt = "### User:\nThomas is healthy, but he has to go to the hospital. What could be the reasons?\n\n### Assistant:\n"
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+del inputs["token_type_ids"]
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+output = model.generate(**inputs, streamer=streamer, use_cache=True, max_new_tokens=float('inf'))
+output_text = tokenizer.decode(output[0], skip_special_tokens=True)
+```
+
 ## Hardware and Software
 
-* **Hardware**: We utilized an A100x8 for training our model
-* **Training Factors**: We fine-tuned this model using a combination of the [DeepSpeed library](https://github.com/microsoft/DeepSpeed) and the [HuggingFace trainer](https://huggingface.co/docs/transformers/main_classes/trainer)
+* **Hardware**: We utilized an A100x8 * 4 for training our model
+* **Training Factors**: We fine-tuned this model using a combination of the [DeepSpeed library](https://github.com/microsoft/DeepSpeed) and the [HuggingFace Trainer](https://huggingface.co/docs/transformers/main_classes/trainer) / [HuggingFace Accelerate](https://huggingface.co/docs/accelerate/index)
 
 ## Evaluation Results
 
@@ -75,15 +102,13 @@ We used the [lm-evaluation-harness repository](https://github.com/EleutherAI/lm-
 | llama-65b | 64.2 | 63.5 | 86.1 | 63.9 | 43.4 | | |
 | falcon-40b-instruct | 63.4 | 61.6 | 84.3 | 55.4 | 52.5 | | |
 
-### Scripts
+### Scripts for H4 Score Reproduction
 - Prepare evaluation environments:
 ```
 # clone the repository
 git clone https://github.com/EleutherAI/lm-evaluation-harness.git
-
 # check out the specific commit
 git checkout b281b0921b636bc36ad05c0b0b0763bd6dd43463
-
 # change to the repository directory
 cd lm-evaluation-harness
 ```