Update README.md

README.md

@@ -7,7 +7,16 @@ tags:
 # Qwen2-1.5B-Instruct-FP8
 
 ## Model Overview
-Qwen2-1.5B-Instruct quantized to FP8 weights and activations using per-tensor quantization, ready for inference with vLLM >= 0.5.0.
+* <h3 style="display: inline;">Model Architecture:</h3> Based on and identical to the Qwen2-1.5B-Instruct architecture
+* <h3 style="display: inline;">Model Optimizations:</h3> Weights and activations quantized to FP8
+* <h3 style="display: inline;">Release Date:</h3> June 14, 2024
+* <h3 style="display: inline;">Model Developers:</h3> Neural Magic
+
+Qwen2-1.5B-Instruct quantized to FP8 weights and activations using per-tensor quantization through the AutoFP8 repository, ready for inference with vLLM >= 0.5.0. 
+Calibrated with 512 UltraChat samples to achieve 99% performance recovery on the Open LLM Benchmark evaluations. 
+Reduces space on disk by ~40%.
+Part of the FP8 LLMs for vLLM collection.
+
 
 ## Usage and Creation
 Produced using [AutoFP8 with calibration samples from ultrachat](https://github.com/neuralmagic/AutoFP8/blob/147fa4d9e1a90ef8a93f96fc7d9c33056ddc017a/example_dataset.py).
@@ -37,8 +46,54 @@ model.quantize(examples)
 model.save_quantized(quantized_model_dir)
 ```
 
+Evaluated through vLLM with the following script:
+
+```
+#!/bin/bash
+
+# Example usage:
+# CUDA_VISIBLE_DEVICES=0 ./eval_openllm.sh "neuralmagic/Qwen2-1.5B-Instruct-FP8" "tensor_parallel_size=1,max_model_len=4096,add_bos_token=True,gpu_memory_utilization=0.7"
+
+export MODEL_DIR=${1}
+export MODEL_ARGS=${2}
+
+declare -A tasks_fewshot=(
+    ["arc_challenge"]=25
+    ["winogrande"]=5
+    ["truthfulqa_mc2"]=0
+    ["hellaswag"]=10
+    ["mmlu"]=5
+    ["gsm8k"]=5
+)
+
+declare -A batch_sizes=(
+    ["arc_challenge"]="auto"
+    ["winogrande"]="auto"
+    ["truthfulqa_mc2"]="auto"
+    ["hellaswag"]="auto"
+    ["mmlu"]=1
+    ["gsm8k"]="auto"
+)
+
+for TASK in "${!tasks_fewshot[@]}"; do
+    NUM_FEWSHOT=${tasks_fewshot[$TASK]}
+    BATCH_SIZE=${batch_sizes[$TASK]}
+    lm_eval --model vllm \
+        --model_args pretrained=$MODEL_DIR,$MODEL_ARGS \
+        --tasks ${TASK} \
+        --num_fewshot ${NUM_FEWSHOT} \
+        --write_out \
+        --show_config \
+        --device cuda \
+        --batch_size ${BATCH_SIZE} \
+        --output_path="results/${TASK}"
+done
+```
+
 ## Evaluation
 
+Evaluated on the Open LLM Leaderboard evaluations through vLLM.
+
 ### Open LLM Leaderboard evaluation scores
 |                      | Qwen2-1.5B-Instruct       | Qwen2-1.5B-Instruct-FP8<br>(this model) |
 | :------------------: | :----------------------: | :------------------------------------------------: |