change id model from drive
Browse files
app.py
CHANGED
|
@@ -4,10 +4,9 @@ import torch
|
|
| 4 |
from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
|
| 5 |
import gradio as gr
|
| 6 |
|
| 7 |
-
# ==== STEP 1: Download model (kalau belum ada) ====
|
| 8 |
os.makedirs("model", exist_ok=True)
|
| 9 |
|
| 10 |
-
MODEL_URL = "https://drive.google.com/uc?id=
|
| 11 |
MODEL_PATH = "model/model.safetensors"
|
| 12 |
|
| 13 |
if not os.path.exists(MODEL_PATH):
|
|
@@ -16,18 +15,14 @@ if not os.path.exists(MODEL_PATH):
|
|
| 16 |
else:
|
| 17 |
print("✅ Model file already exists")
|
| 18 |
|
| 19 |
-
# ==== STEP 2: Load tokenizer & model ====
|
| 20 |
print("🔧 Loading model & tokenizer...")
|
| 21 |
tokenizer = AutoTokenizer.from_pretrained("model")
|
| 22 |
model = AutoModelForCausalLM.from_pretrained("model", torch_dtype=torch.float16)
|
| 23 |
|
| 24 |
-
# Gunakan CUDA kalau tersedia
|
| 25 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
| 26 |
model.to(device)
|
| 27 |
-
# Optional: streaming token
|
| 28 |
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
|
| 29 |
|
| 30 |
-
# ==== STEP 3: Define response logic ====
|
| 31 |
def respond(message, history, max_tokens, temperature, top_p):
|
| 32 |
input_ids = tokenizer.encode(message, return_tensors="pt").to(device)
|
| 33 |
history_text = ""
|
|
|
|
| 4 |
from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
|
| 5 |
import gradio as gr
|
| 6 |
|
|
|
|
| 7 |
os.makedirs("model", exist_ok=True)
|
| 8 |
|
| 9 |
+
MODEL_URL = "https://drive.google.com/uc?id=1Kg8KSGIgjBopeOKSbYbFWEgUlYOcqyXX" # <- Ganti file ID-nya
|
| 10 |
MODEL_PATH = "model/model.safetensors"
|
| 11 |
|
| 12 |
if not os.path.exists(MODEL_PATH):
|
|
|
|
| 15 |
else:
|
| 16 |
print("✅ Model file already exists")
|
| 17 |
|
|
|
|
| 18 |
print("🔧 Loading model & tokenizer...")
|
| 19 |
tokenizer = AutoTokenizer.from_pretrained("model")
|
| 20 |
model = AutoModelForCausalLM.from_pretrained("model", torch_dtype=torch.float16)
|
| 21 |
|
|
|
|
| 22 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
| 23 |
model.to(device)
|
|
|
|
| 24 |
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
|
| 25 |
|
|
|
|
| 26 |
def respond(message, history, max_tokens, temperature, top_p):
|
| 27 |
input_ids = tokenizer.encode(message, return_tensors="pt").to(device)
|
| 28 |
history_text = ""
|