Update README.md

README.md

@@ -6,17 +6,50 @@ tags:
 - peft
 library_name: transformers
 widget:
-  - messages:
-      - role: user
-        content: What is your favorite condiment?
+- messages:
+  - role: user
+    content: What is your favorite condiment?
 license: other
+datasets:
+- timdettmers/openassistant-guanaco
+language:
+- en
 ---
+# Model Details
+
+This model is a finetuned Meta-Llama-3-8b-Instruct model on the openassistant dataset. It was finetuned using PEFT, a library for efficiently adapting pre-trained language models to various downstream applications without fine-tuning all the model’s parameters.
+
+# Inference with PEFT Models:
+
+```python
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel, PeftConfig
+
+base_model = "meta-llama/Meta-Llama-3-8B"
+adapter_model = "pantelnm/llama3-openassistant"
+
+prompt = "Write your prompt here!"
+
+model = AutoModelForCausalLM.from_pretrained(base_model)
+model = PeftModel.from_pretrained(model, adapter_model)
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+
+model = model.to("cuda")
+model.eval()
+
+inputs = tokenizer(prompt, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model.generate(input_ids=inputs["input_ids"].to("cuda"), max_new_tokens=10)
+    print(tokenizer.batch_decode(outputs.detach().cpu().numpy(), skip_special_tokens=True)[0])
+```
 
 # Model Trained Using AutoTrain
 
 This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
 
-# Usage
+# General Usage
 
 ```python