first commit

app.py

@@ -0,0 +1,30 @@
+import streamlit as st
+from transformers import AutoModelForCausalLM, LlamaTokenizer
+
+
+@st.cache_resource
+def load():
+    model = AutoModelForCausalLM.from_pretrained(
+    "stabilityai/japanese-stablelm-instruct-alpha-7b",
+    trust_remote_code=True,
+    )
+    tokenizer = LlamaTokenizer.from_pretrained(
+        "novelai/nerdstash-tokenizer-v1", 
+        additional_special_tokens=['▁▁'],
+        )
+    return model, tokenizer
+
+def generate():
+    pass
+
+
+st.header(":dna: 遺伝カウンセリング対話AI")
+
+st.sidebar.header("Options")
+st.session_state["options"]["temperature"] = st.sidebar.slider("temperature", min_value=0.0, max_value=2.0, step=0.1, value=st.session_state["options"]["temperature"])
+st.session_state["options"]["top_k"] = st.sidebar.slider("top_k", min_value=0, max_value=100, step=1, value=st.session_state["options"]["top_k"])
+st.session_state["options"]["top_p"] = st.sidebar.slider("top_p", min_value=0.0, max_value=1.0, step=0.1, value=st.session_state["options"]["top_p"])
+st.session_state["options"]["repetition_penalty"] = st.sidebar.slider("repetition_penalty", min_value=1.0, max_value=2.0, step=0.01, value=st.session_state["options"]["repetition_penalty"])
+st.session_state["options"]["system_prompt"] = st.sidebar.text_area("System Prompt", value=st.session_state["options"]["system_prompt"])
+
+model, tokenizer = load()

requirements.txt

@@ -0,0 +1,9 @@
+streamlit>=1.26.0
+torch==2.0.0
+transformers>=4.33.1
+peft>=0.5.0
+sentencepiece>=0.1.99
+einops>=0.6.1
+bitsandbytes>=0.41.1
+scipy>=1.11.2
+accelerate>=0.22.0