Update README.md
Browse files
README.md
CHANGED
|
@@ -6,12 +6,24 @@ license_link: https://huggingface.co/Qwen/Qwen2-72B/blob/main/LICENSE
|
|
| 6 |
|
| 7 |
|
| 8 |
|
|
|
|
| 9 |
|
|
|
|
| 10 |
|
| 11 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
| 12 |
|
|
|
|
|
|
|
| 13 |
|
| 14 |
|
| 15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
|
| 17 |
-
|
|
|
|
| 6 |
|
| 7 |
|
| 8 |
|
| 9 |
+
# Tess-v2.5-Qwen2-72B
|
| 10 |
|
| 11 |
+
We've created Tess-v2.5-Qwen2-72B, the latest state-of-the-art model in the Tess series of Large Language Models (LLMs). Tess, short for Tesoro (<em>Treasure</em> in Italian), is the flagship LLM series created by Migel Tissera. Tess-v2.5 brings significant improvements in reasoning capabilities, coding capabilities and mathematics. It is currently the #1 ranked open weight model when evaluated on MMLU (Massive Multitask Language Understanding). It scores higher than all other open weight models including Qwen2-72B-Instruct, Llama3-70B-Instruct, Mixtral-8x22B-Instruct and DBRX-Instruct. Further, when evaluated on MMLU, Tess-v2.5-Qwen2-72B model outperforms even the frontier closed models Gemini-1.0-Ultra, Gemini-1.5-Pro, Mistral-Large and Claude-3-Sonnet.
|
| 12 |
|
| 13 |
+
Tess-v2.5-Qwen2-72B was fine-tuned over the Qwen2-72B base, using the Tess-v2.5 dataset that contains 300K samples spanning multiple topics, including business and management, marketing, history, social sciences, arts,STEM subjects and computer programming. This dataset was synthetically generated with the [Sensei](https://github.com/migtissera/Sensei) framework, using multiple frontier models such as GPT-4-Turbo, Claude-Opus and Mistral-Large.
|
| 14 |
+
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
# Evaluation
|
| 18 |
|
| 19 |
+
## MMLU (Massive Multitask Language Understanding)
|
| 20 |
+
|
| 21 |
|
| 22 |
|
| 23 |
|
| 24 |
+
## AGIEval
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
|
| 29 |
|
|
|