app.py

import streamlit as st
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)



# 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)