Update README.md
Browse files
README.md
CHANGED
@@ -26,7 +26,7 @@ base_model: meta-llama/Meta-Llama-3.1-405B-Instruct
|
|
26 |
- **Model Developers:** Neural Magic
|
27 |
|
28 |
Quantized version of [Meta-Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct) with the updated 8 kv-heads.
|
29 |
-
It achieves an average score of 86.
|
30 |
|
31 |
### Model Optimizations
|
32 |
|
@@ -165,7 +165,7 @@ oneshot(
|
|
165 |
|
166 |
The model was evaluated on MMLU, ARC-Challenge, GSM-8K, Hellaswag, Winogrande and TruthfulQA.
|
167 |
Evaluation was conducted using the Neural Magic fork of [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness/tree/llama_3.1_instruct) (branch llama_3.1_instruct) and the [vLLM](https://docs.vllm.ai/en/stable/) engine.
|
168 |
-
This version of the lm-evaluation-harness includes versions of ARC-Challenge, GSM-8K, and MMLU that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-8B-Instruct-evals).
|
169 |
|
170 |
### Accuracy
|
171 |
|
@@ -191,6 +191,16 @@ This version of the lm-evaluation-harness includes versions of ARC-Challenge, GS
|
|
191 |
<td>99.59%
|
192 |
</td>
|
193 |
</tr>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
194 |
<tr>
|
195 |
<td>ARC Challenge (0-shot)
|
196 |
</td>
|
@@ -244,11 +254,11 @@ This version of the lm-evaluation-harness includes versions of ARC-Challenge, GS
|
|
244 |
<tr>
|
245 |
<td><strong>Average</strong>
|
246 |
</td>
|
247 |
-
<td><strong>86.
|
248 |
</td>
|
249 |
-
<td><strong>86.
|
250 |
</td>
|
251 |
-
<td><strong>99.
|
252 |
</td>
|
253 |
</tr>
|
254 |
</table>
|
@@ -270,6 +280,17 @@ lm_eval \
|
|
270 |
--batch_size auto
|
271 |
```
|
272 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
273 |
#### ARC-Challenge
|
274 |
```
|
275 |
lm_eval \
|
|
|
26 |
- **Model Developers:** Neural Magic
|
27 |
|
28 |
Quantized version of [Meta-Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct) with the updated 8 kv-heads.
|
29 |
+
It achieves an average score of 86.60 on the [OpenLLM](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) benchmark (version 1), whereas the unquantized model achieves 86.79.
|
30 |
|
31 |
### Model Optimizations
|
32 |
|
|
|
165 |
|
166 |
The model was evaluated on MMLU, ARC-Challenge, GSM-8K, Hellaswag, Winogrande and TruthfulQA.
|
167 |
Evaluation was conducted using the Neural Magic fork of [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness/tree/llama_3.1_instruct) (branch llama_3.1_instruct) and the [vLLM](https://docs.vllm.ai/en/stable/) engine.
|
168 |
+
This version of the lm-evaluation-harness includes versions of ARC-Challenge, GSM-8K, MMLU, and MMLU-cot that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-8B-Instruct-evals).
|
169 |
|
170 |
### Accuracy
|
171 |
|
|
|
191 |
<td>99.59%
|
192 |
</td>
|
193 |
</tr>
|
194 |
+
<tr>
|
195 |
+
<td>MMLU-cot (0-shot)
|
196 |
+
</td>
|
197 |
+
<td>88.11
|
198 |
+
</td>
|
199 |
+
<td>87.87
|
200 |
+
</td>
|
201 |
+
<td>99.73%
|
202 |
+
</td>
|
203 |
+
</tr>
|
204 |
<tr>
|
205 |
<td>ARC Challenge (0-shot)
|
206 |
</td>
|
|
|
254 |
<tr>
|
255 |
<td><strong>Average</strong>
|
256 |
</td>
|
257 |
+
<td><strong>86.79</strong>
|
258 |
</td>
|
259 |
+
<td><strong>86.60</strong>
|
260 |
</td>
|
261 |
+
<td><strong>99.74%</strong>
|
262 |
</td>
|
263 |
</tr>
|
264 |
</table>
|
|
|
280 |
--batch_size auto
|
281 |
```
|
282 |
|
283 |
+
#### MMLU-cot
|
284 |
+
```
|
285 |
+
lm_eval \
|
286 |
+
--model vllm \
|
287 |
+
--model_args pretrained="neuralmagic/Meta-Llama-3.1-405B-Instruct-FP8",dtype=auto,add_bos_token=True,max_model_len=4096,max_gen_toks=1024,tensor_parallel_size=8 \
|
288 |
+
--tasks mmlu_cot_0shot_llama_3.1_instruct \
|
289 |
+
--apply_chat_template \
|
290 |
+
--num_fewshot 0 \
|
291 |
+
--batch_size auto
|
292 |
+
```
|
293 |
+
|
294 |
#### ARC-Challenge
|
295 |
```
|
296 |
lm_eval \
|