Update README.md

README.md

@@ -7,6 +7,7 @@ language:
 library_name: peft
 tags:
 - medical
+pipeline_tag: question-answering
 ---
 
 # Model Card for GaiaMiniMed
@@ -83,14 +84,26 @@ tokenizer = AutoTokenizer.from_pretrained(base_model_id, trust_remote_code=True,
 tokenizer.pad_token = tokenizer.eos_token
 tokenizer.padding_side = 'left'
 
+# Define the PeftConfig
+#peft_config = PeftConfig(
+#    max_length=500,
+#    use_cache=True,
+#    early_stopping=False,
+#    bos_token_id=tokenizer.bos_token_id,  # Use the tokenizer's BOS token ID
+#    eos_token_id=tokenizer.eos_token_id,  # Use the tokenizer's EOS token ID
+#    pad_token_id=tokenizer.eos_token_id,  # Use the tokenizer's EOS token ID
+#    temperature=0.4,
+#    do_sample=True
+#)
 
 
 # Load the GaiaMiniMed model with the specified configuration
+# Load the Peft model with a specific configuration
 # Specify the configuration class for the model
-model_config = AutoConfig.from_pretrained(base_model_id)
+model_config = PeftConfig.from_pretrained(model_directory) #use base falcon config
 # Load the PEFT model with the specified configuration
 peft_model = AutoModelForCausalLM.from_pretrained(base_model_id, config=model_config)
-peft_model = PeftModel.from_pretrained("Tonic/GaiaMiniMed")
+peft_model = PeftModel.from_pretrained(model="Tonic/GaiaMiniMed")
 peft_model = PeftModel.from_pretrained(peft_model, "Tonic/GaiaMiniMed")