Update README.md

README.md

@@ -9,6 +9,8 @@ model = PeftModel.from_pretrained('lamm-mit/BioinspiredLLM')
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 ```
 
+Variants of the model are included, featuring various GGUF versions for use withm llama.cpp, for instance. 
+
 Generate:
 ```
 device='cuda'
@@ -38,3 +40,24 @@ def generate_response (text_input="Biological materials offer amazing",
                                   )
     return tokenizer.batch_decode(outputs[:,inputs.shape[1]:].detach().cpu().numpy(), skip_special_tokens=True)
 ```
+Generation example:
+```
+system_prompt = "You are BioinspiredLLM. You are knowledgeable in biological and bio-inspired materials and provide accurate and qualitative insights about biological materials found in Nature. You are a cautious assistant. You think step by step. You carefully follow instructions."
+user_message = "What are hierarchical, biological materials?"
+
+txt =  f"<|im_start|>system\n{system_prompt}<|im_end|>\n<|im_start|>user\n{user_message}<|im_end|>\n<|im_start|>assistant"
+
+# modulate temperature(0.1-1.0) to adjust 'creativity'
+# modulate max_new_tokens to change length of generated response 
+output_text=generate_response ( text_input=txt,eos_token_id=2,
+                                num_return_sequences=1,
+                                repetition_penalty=1.1,
+                                top_p=0.95,
+                                top_k=50, 
+                                temperature=0.1,
+                                max_new_tokens=512,
+                                verbatim=False, 
+                              )
+
+print(output_text)
+```