Updates readme

README.md

@@ -14,7 +14,7 @@ model-index:
 ---
 
 
-# sft
+# Supervised Fine-Tuned Model
 
 This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the open_platypus dataset.
 It achieves the following results on the evaluation set:
@@ -23,15 +23,30 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the open_platypus dataset.
 
 ## Intended uses & limitations
 
-More information needed
+### How to use
+
+You can use this model directly with a pipeline for text classification. Here is an example:
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("2nji/llama3-platypus")
+model = AutoModel.from_pretrained("2nji/llama3-platypus")
+
+inputs = tokenizer("Example input text", return_tensors="pt")
+with torch.no_grad():
+    outputs = model(**inputs)
+
+print(outputs)
+```
 
 ## Training and evaluation data
 
-More information needed
+The model was fine-tuned on the open_platypus dataset.
 
 ## Training procedure
 
@@ -51,10 +66,12 @@ The following hyperparameters were used during training:
 
 ### Training results
 
+The model was trained on a single NVIDIA H100 GPU with the following results:
+- Loss: 0.6769
+- Accuracy: 0.8116
 
 
 ### Framework versions
-
 - PEFT 0.11.1
 - Transformers 4.42.3
 - Pytorch 2.3.1+cu121