Update README.md

README.md

@@ -2,7 +2,7 @@
 datasets:
 - NeelNanda/pile-10k
 base_model:
-- deepseek-ai/DeepSeek-R1
+- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
 
 
 
@@ -160,42 +160,30 @@ pip3 install lm-eval==0.4.7
 ```bash
 lm-eval --model hf --model_args pretrained=OPEA/DeepSeek-R1-Distill-Qwen-32B-int4-sym-inc   --tasks leaderboard_mmlu_pro,leaderboard_ifeval,lambada_openai,hellaswag,piqa,winogrande,truthfulqa_mc1,openbookqa,boolq,arc_easy,arc_challenge,mmlu,gsm8k --batch_size 16
 ```
-|           Metric           |   BF16(lm-eval==0.4.7)    |      INT4      |
+|           Metric           |   BF16   |      INT4      |
 | :------------------------: | :----------------------: | :---------------: |
-|            avg             |          |                   |
-| leaderboard_mmlu_pro 5shot |          |                   |
-|            mmlu            |          |       |
-|       lambada_openai       |          |       |
-|         hellaswag          |          |       |
-|         winogrande         |          |       |
-|            piqa            |          |       |
-|       truthfulqa_mc1       |          |       |
-|         openbookqa         |          |       |
-|           boolq            |          |       |
-|          arc_easy          |          |       |
-|     leaderboard_ifeval     |          |       | 
-|       arc_challenge        |          |       |
-| gsm8k(5shot) strict match  |          |       |
+| avg                  | 0.6647 |  0.6639|
+|----------------------|--------|--------|
+| leaderboard_mmlu_pro | -      | -      |
+| mmlu                 | 0.7964 | 0.7928 |
+| lambada_openai       | 0.6649 | 0.6718 |
+| hellaswag            | 0.6292 | 0.6223 |
+| winogrande           | 0.7482 | 0.7482 |
+| piqa                 | 0.8058 | 0.7982 |
+| truthfulqa_mc1       | 0.3831 | 0.3905 |
+| openbookqa           | 0.3520 | 0.3520 |
+| boolq                | 0.8963 | 0.8972 |
+| arc_easy             | 0.8207 | 0.8194 |
+| arc_challenge        | 0.5503 | 0.5469 |
+| leaderboard_ifeval   | -      | -      |
+| gsm8k                | -      | -      |
+
 
 
 ### Generate the model
 
-~~~python
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import transformers
+~~~bash
 
-model_name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True, torch_dtype="auto")
-device_map = "auto"
-
-from auto_round import AutoRound
-autoround = AutoRound(model=model, tokenizer=tokenizer, device_map=device_map, nsamples=512,
-                      batch_size=4, seqlen=2048,
-                      )
-autoround.quantize()
-autoround.save_quantized(format="auto_gptq", output_dir="tmp_autoround")
 
 ~~~