Update README.md

Gradio code updated

README.md

@@ -99,16 +99,14 @@ Output: Bullish:38751.32,38818.6,38818.6,38695.03
 import sys
 import torch
 from peft import PeftModel
-import transformers
+from transformers import (
+    LlamaTokenizer, 
+    LlamaForCausalLM, 
+    GenerationConfig
+)
 import gradio as gr
 
-assert (
-    "LlamaTokenizer" in transformers._import_structure["models.llama"]
-), "LLaMA is now in HuggingFace's main branch.\nPlease reinstall it: pip uninstall transformers && pip install git+https://github.com/huggingface/transformers.git"
-from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig
-
-
-SHARE_GRADIO=True
+SHARE_GRADIO = True
 LOAD_8BIT = False
 
 BASE_MODEL = "mrzlab630/weights_Llama_7b"
@@ -116,16 +114,9 @@ LORA_WEIGHTS = "mrzlab630/lora-alpaca-trading-candles"
 
 tokenizer = LlamaTokenizer.from_pretrained(BASE_MODEL)
 
-if torch.cuda.is_available():
-    device = "cuda"
-else:
-    device = "cpu"
-
-try:
-    if torch.backends.mps.is_available():
-        device = "mps"
-except:
-    pass
+device = "cuda" if torch.cuda.is_available() else "cpu"
+if torch.backends.mps.is_available():
+    device = "mps"
 
 if device == "cuda":
     model = LlamaForCausalLM.from_pretrained(
@@ -161,6 +152,12 @@ else:
         device_map={"": device},
     )
 
+if not LOAD_8BIT:
+    model.half()
+
+model.eval()
+if torch.__version__ >= "2" and sys.platform != "win32":
+    model = torch.compile(model)
 
 def generate_prompt(instruction, input=None):
     if input:
@@ -181,14 +178,6 @@ def generate_prompt(instruction, input=None):
 
 ### Response:"""
 
-if not LOAD_8BIT:
-    model.half()  # seems to fix bugs for some users.
-
-model.eval()
-if torch.__version__ >= "2" and sys.platform != "win32":
-    model = torch.compile(model)
-
-
 def evaluate(
     instruction,
     input=None,
@@ -221,31 +210,22 @@ def evaluate(
     output = tokenizer.decode(s)
     return output.split("### Response:")[1].strip()
 
-
 gr.Interface(
     fn=evaluate,
     inputs=[
-        gr.components.Textbox(
-            lines=2, label="Instruction", placeholder="Tell me about alpacas."
-        ),
-        gr.components.Textbox(lines=2, label="Input", placeholder="none"),
-        gr.components.Slider(minimum=0, maximum=1, value=0.1, label="Temperature"),
-        gr.components.Slider(minimum=0, maximum=1, value=0.75, label="Top p"),
-        gr.components.Slider(minimum=0, maximum=100, step=1, value=40, label="Top k"),
-        gr.components.Slider(minimum=1, maximum=4, step=1, value=4, label="Beams"),
-        gr.components.Slider(
-            minimum=1, maximum=2000, step=1, value=128, label="Max tokens"
-        ),
-    ],
-    outputs=[
-        gr.inputs.Textbox(
-            lines=5,
-            label="Output",
-        )
+        gr.Textbox(lines=2, label="Instruction", placeholder="Tell me about alpacas."),
+        gr.Textbox(lines=2, label="Input", placeholder="none"),
+        gr.Slider(minimum=0, maximum=1, value=0.1, label="Temperature"),
+        gr.Slider(minimum=0, maximum=1, value=0.75, label="Top p"),
+        gr.Slider(minimum=0, maximum=100, step=1, value=40, label="Top k"),
+        gr.Slider(minimum=1, maximum=4, step=1, value=4, label="Beams"),
+        gr.Slider(minimum=1, maximum=2000, step=1, value=128, label="Max tokens"),
     ],
+    outputs=gr.Textbox(lines=5, label="Output"),
     title="💹 🕯 Alpaca-LoRA-Trading-Candles",
-    description="Alpaca-LoRA-Trading-Candles is a 7B-parameter LLaMA model tuned to execute instructions. It is trained on the [trading candles] dataset(https://huggingface.co/datasets/mrzlab630/trading-candles) and uses the Huggingface LLaMA implementation. For more information, visit [project website](https://huggingface.co/mrzlab630/lora-alpaca-trading-candles).\nPrompts:\nInstruction: identify candle, Input: open:241.5,close:232.9, high:241.7, low:230.8\nInstruction: find candle, Input: 38811.24,38838.41,38846.71,38736.24,234.00,45275276.00,59816.00,441285.00,645.00,84176.00,1694619.00,15732335.00\nInstruction: find candle: Bullish, Input: 38751.32,38818.6,38818.6,38695.03,62759348.00,2605789.00,71030.00,820738.00,59659.00,724738.00,7368363.00,50654.00",
+    description="""Alpaca-LoRA-Trading-Candles is a 7B-parameter LLaMA model tuned to execute instructions. It is trained on the [trading candles](https://huggingface.co/datasets/mrzlab630/trading-candles) dataset and uses the Huggingface LLaMA implementation. For more information, visit [project website](https://huggingface.co/mrzlab630/lora-alpaca-trading-candles).""",
 ).launch(server_name="0.0.0.0", share=SHARE_GRADIO)
 
 
+
 ```