Update README.md

README.md

@@ -11,12 +11,52 @@ language:
 - en
 ---
 
+# Disclaimer!!
+Hello! This model is not perfect yet, I am just experimenting! 
+This is me attempting the [AIMO Prize 2 Kaggle contest](https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-2)
+
+I have decided to release the models before the competition ends because I don't care about winning the contest as much!
+
+My research fields are Medical Computing and Reinforcement Learning. Feel free to add me on [LinkedIn](https://www.linkedin.com/in/sindhusatish/) if you want to chat!
+
 # Uploaded  model
 
 - **Developed by:** sindhusatish97
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/DeepSeek-R1-Distill-Qwen-14B
 
-This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. - Huge thanks to the awesome team for releasing these distilled models!
 
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+
+
+# Inference
+```python
+
+!pip install unsloth
+# Also get the latest nightly Unsloth!
+!pip install --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth.git
+from unsloth import FastLanguageModel
+import torch
+max_seq_length = 5120 # I chose this value based on Qwen's max sequence length.  
+dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
+load_in_4bit = True
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "sindhusatish97/DeepSeek-R1-Distill-Qwen-14B-unsloth-bnb-4bit-AIMO_CoT",
+    max_seq_length = max_seq_length,
+    dtype = dtype,
+    load_in_4bit = load_in_4bit,
+    # token = "hf_...", # use one if using gated models like meta-llama/Llama-2-7b-hf
+)
+FastLanguageModel.for_inference(model)
+inputs = tokenizer(
+[
+        """4 pints of a 5% antifreeze solution and 8 pints of a 20% antifreeze solution must be mixed to obtain 12 pints of a 
+        solution with what percentage of antifreeze?"""
+], return_tensors = "pt").to("cuda")
+
+from transformers import TextStreamer
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer, max_length = 2048)
+```