Update README.md

README.md

@@ -14,3 +14,42 @@ datasets:
 license_name: gemma-terms-of-use
 license_link: https://ai.google.dev/gemma/terms
 ---
+
+# Code-Gemma-2B
+ accelarate
+### Description
+Code-Gemma was finetuned on the CodeAlpaca-20k dataset using the unsloth library to enhance the Gemma-2B-it model.
+
+### Usage
+
+Below we share some code snippets on how to get quickly started with running the model.
+
+```python
+!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
+if major_version >= 8:
+    # Use this for new GPUs like Ampere, Hopper GPUs (RTX 30xx, RTX 40xx, A100, H100, L40)
+    !pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
+else:
+    # Use this for older GPUs (V100, Tesla T4, RTX 20xx)
+    !pip install --no-deps xformers trl peft accelerate bitsandbytes
+pass
+```
+
+#### Running the model on a GPU using different precisions
+
+* _Using `torch.float16`_
+
+```python
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("Praneeth/code-gemma-2b-it")
+model = AutoModelForCausalLM.from_pretrained("Praneeth/code-gemma-2b-it", device_map="auto", torch_dtype=torch.float16)
+
+input_text = "Write me a poem about Machine Learning."
+input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
+
+outputs = model.generate(**input_ids)
+print(tokenizer.decode(outputs[0]))
+```
+