Update README.md

README.md

@@ -12,6 +12,9 @@ Hammer-7b is a cutting-edge Large Language Model (LLM) crafted to boost the crit
 ## Model Details
 Hammer-7b is a finetuned model built upon [Qwen2-7B-Instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct). It's trained using the [APIGen Function Calling Datasets](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) containing 60,000 samples, supplemented by 7,500 irrelevance detection data we generated. Employing innovative training techniques like function masking, function shuffling, and prompt optimization, Hammer-7b has achieved exceptional performances across numerous benchmarks including [Berkley Function Calling Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html), [API-Bank](https://arxiv.org/abs/2304.08244), [Tool-Alpaca](https://arxiv.org/abs/2306.05301), [Nexus Raven](https://github.com/nexusflowai/NexusRaven-V2) and [Seal-Tools](https://arxiv.org/abs/2405.08355).
 
+## Tuning Details
+Thanks so much for your attention, a report with all the technical details leading to our models will be published soon.
+
 ## Evaluation
 First, we evaluate Hammer-7b on the Berkeley Function-Calling Leaderboard (BFCL):