This is a passthrough of arco with an experimental model. It improved on arc challenge, only missing 1.2 points to get to the level of modern 3b baseline performance.
If you prefer answering multilingual, general knowledge, trivially simple questions chose qwen or llama. If you prefer solving trivially simple english tasks while being half the size, chose arco.
prompt
there is no prompt intentionally set.
benchmarks
zero-shot results from state-of-the-art small language models
Parameters
Model
MMLU
ARC-C
HellaSwag
PIQA
Winogrande
Average
0.5b
qwen 2
44.13
28.92
49.05
69.31
56.99
49.68
0.5b
qwen 2.5
47.29
31.83
52.17
70.29
57.06
51.72
0.5b
arco
26.17
37.29
62.88
74.37
62.27
52.60
0.5b
arco 2
25.51
38.82
63.02
74.70
61.25
52.66
1.24b
llama 3.2
36.75
36.18
63.70
74.54
60.54
54.34
supporters
trivia
arco also means "arc optimized" hence the focus on this cognitive-based benchmark.
Runs of appvoid arco-2 on huggingface.co
35
Total runs
-5
24-hour runs
-8
3-day runs
-19
7-day runs
-2
30-day runs
More Information About arco-2 huggingface.co Model
arco-2 huggingface.co is an AI model on huggingface.co that provides arco-2's model effect (), which can be used instantly with this appvoid arco-2 model. huggingface.co supports a free trial of the arco-2 model, and also provides paid use of the arco-2. Support call arco-2 model through api, including Node.js, Python, http.
arco-2 huggingface.co is an online trial and call api platform, which integrates arco-2's modeling effects, including api services, and provides a free online trial of arco-2, you can try arco-2 online for free by clicking the link below.
arco-2 is an open source model from GitHub that offers a free installation service, and any user can find arco-2 on GitHub to install. At the same time, huggingface.co provides the effect of arco-2 install, users can directly use arco-2 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.