Update app.py

app.py

@@ -1,16 +1,28 @@
 import streamlit as st
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-model_id = "Mykes/med_gemma7b_gguf"
-filename = "unsloth.Q4_K_M.gguf"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id, gguf_file=filename)
-model = AutoModelForCausalLM.from_pretrained(model_id, gguf_file=filename)
-
-
+from ctransformers import AutoModelForCausalLM, AutoTokenizer
 
+model = AutoModelForCausalLM.from_pretrained("Mykes/med_gemma7b_gguf", model_file="unsloth.Q4_K_M.gguf")
+tokenizer = AutoTokenizer.from_pretrained(model)
 input_text = st.textarea('text')
 if text:
     input_ids = tokenizer(input_text, return_tensors="pt")
     outputs = model.generate(**input_ids)
-    st.write(outputs)
+    st.write(outputs)
+
+
+
+# from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# model_id = "Mykes/med_gemma7b_gguf"
+# filename = "unsloth.Q4_K_M.gguf"
+
+# tokenizer = AutoTokenizer.from_pretrained(model_id, gguf_file=filename)
+# model = AutoModelForCausalLM.from_pretrained(model_id, gguf_file=filename)
+
+
+
+# input_text = st.textarea('text')
+# if text:
+#     input_ids = tokenizer(input_text, return_tensors="pt")
+#     outputs = model.generate(**input_ids)
+#     st.write(outputs)