Update README.md

README.md

@@ -11,6 +11,49 @@ It was fine-tuned on several thousand astronomy abstracts collected on Arxiv.
 
 ## Model Details
 
+```{python}
+from transformers import AutoModelForCausalLM
+
+online_model = AutoModelForCausalLM.from_pretrained("charlieoneill/falcon-7b-abstracts-2190", trust_remote_code=True)
+
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-7b")
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=online_model,
+    tokenizer=tokenizer,
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+    device_map="auto",
+)
+
+sequences = pipeline(
+   "### Instruction: Generate a scientific hypothesis about astronomy in the style of an Arxiv paper.\n ### Hypothesis:",
+    max_length=500,
+    do_sample=True,
+    top_k=10,
+    num_return_sequences=1,
+    eos_token_id=tokenizer.eos_token_id,
+)
+
+def format_output(output):
+    output = output.replace("\n", " ")  # Replace newline characters with spaces
+    output = output.replace("\\n", " ")
+    parts = output.split("###")  # Split string at '###'
+    
+    # Get and clean instruction part
+    instruction = parts[1].strip() 
+    
+    # Get and clean hypothesis part
+    hypothesis = parts[2].strip()  
+    
+    # Format the output
+    formatted_output = f"{instruction}\n\n{hypothesis}"
+    
+    return formatted_output
+
+format_output(sequences[0]['generated_text'])
+```
+
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->