Update README.md

README.md

@@ -26,7 +26,7 @@ The models in the LH-Tech AI Pin Series are very small models that were trained
 | Pin-15M | 14.84M | 1500 | 2.358367 | Low | It is hard to see your plans when you want to enjoy the day. |
 | Pin-20M | 21.03M | 1500 | 2.217588 | Medium | Yes, sunny days are wonderful! I love hearing about the sunshine and the sun's shining on. |
 | Pin-25M | 26.76M | 1500 | 2.139837 | Medium | Sunny days make everything look brighter, especially with a nice friend who cares. |
-| Pin-Ultra-25M | 26.76M | 8000 | ... | ... | Coming soon... |
+| Pin-Ultra-25M | 26.76M | 8000 | 1.588281 | Hight | Yes, I spent some time at the park and was looking for a new collar. |
 
 \* All models were prompted with `What is the weather like today?`.
 
@@ -51,7 +51,7 @@ You can find the full training code for the Pin Model Series in this repo.<br>
 Have fun :D
 
 ### Training details
-We trained all these models in ~30 minutes on a single T4 GPU in a Kaggle Session.<br>
+We trained all these models in ~30 minutes on Kaggle 2xT4 GPU in a Kaggle Session (except for Pin-Ultra-25 - it trained for ~4 hours on Kaggle 2xT4).<br>
 So you are able to easily recreate all of the Pin model without having to launch a 8xH100 cluster 😂
 
 ## How to use the model
@@ -60,7 +60,7 @@ You can easily use the favorite model of the Pin series like this:
 1. Download `use.py` from this repo.
 2. Adjust the subfolder argument here:
    ```python
-   answer = run_pin_inference(user_query, model_id="LH-Tech-AI/Pin", subfolder="Pin-25M") # use your favorite model here, e.g. "Pin-25M" or "Pin-15M"...
+   answer = run_pin_inference(user_query, model_id="LH-Tech-AI/Pin", subfolder="Pin-Ultra-25M") # use your favorite model here, e.g. "Pin-25M" or "Pin-15M"...
    ```
 3. Adjust the input prompt here:
    ```python
@@ -73,5 +73,5 @@ You can easily use the favorite model of the Pin series like this:
 ...to:
 
 - HF Transformers
-- Kaggle for the T4 GPU
+- Kaggle for the 2xT4 GPU
 - starhopp3r for his TinyChat dataset