Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -5,22 +5,22 @@ from typing import Iterator
|
|
5 |
import gradio as gr
|
6 |
import spaces
|
7 |
import torch
|
8 |
-
from transformers import
|
9 |
|
10 |
MAX_MAX_NEW_TOKENS = 2048
|
11 |
DEFAULT_MAX_NEW_TOKENS = 1024
|
12 |
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
|
13 |
|
14 |
DESCRIPTION = """\
|
15 |
-
# ZhongJing
|
16 |
-
This Space demonstrates model [
|
17 |
"""
|
18 |
|
19 |
LICENSE = """
|
20 |
<p/>
|
21 |
---
|
22 |
-
As a
|
23 |
-
this demo is governed by the original [license](https://huggingface.co/CMLL/ZhongJing-2-1_8b-merge/LICENSE).
|
24 |
"""
|
25 |
|
26 |
if not torch.cuda.is_available():
|
@@ -28,7 +28,7 @@ if not torch.cuda.is_available():
|
|
28 |
|
29 |
if torch.cuda.is_available():
|
30 |
model_id = "CMLL/ZhongJing-2-1_8b-merge"
|
31 |
-
|
32 |
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
33 |
tokenizer.use_default_system_prompt = False
|
34 |
|
@@ -36,50 +36,50 @@ if torch.cuda.is_available():
|
|
36 |
def generate(
|
37 |
message: str,
|
38 |
chat_history: list[tuple[str, str]],
|
39 |
-
system_prompt: str
|
40 |
max_new_tokens: int = 1024,
|
41 |
temperature: float = 0.6,
|
42 |
top_p: float = 0.9,
|
43 |
top_k: int = 50,
|
44 |
repetition_penalty: float = 1.2,
|
45 |
) -> Iterator[str]:
|
46 |
-
conversation = [
|
|
|
|
|
47 |
for user, assistant in chat_history:
|
48 |
conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
|
49 |
conversation.append({"role": "user", "content": message})
|
50 |
|
51 |
-
|
|
|
|
|
|
|
|
|
52 |
|
53 |
-
|
54 |
-
|
55 |
-
"
|
56 |
-
|
57 |
-
|
58 |
-
|
59 |
-
|
60 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
61 |
|
62 |
-
# Function to run the generation
|
63 |
-
def run_generation():
|
64 |
-
try:
|
65 |
-
results = pipe(input_text, **generate_kwargs)
|
66 |
-
return results
|
67 |
-
except Exception as e:
|
68 |
-
return [f"Error in generation: {e}"]
|
69 |
-
|
70 |
-
# Run generation in a separate thread and wait for it to finish
|
71 |
outputs = []
|
72 |
-
|
73 |
-
|
74 |
-
|
75 |
-
|
76 |
-
for output in outputs:
|
77 |
-
yield output['generated_text'] if isinstance(output, dict) else output
|
78 |
|
79 |
chat_interface = gr.ChatInterface(
|
80 |
fn=generate,
|
81 |
additional_inputs=[
|
82 |
-
gr.Textbox(label="System prompt", lines=6
|
83 |
gr.Slider(
|
84 |
label="Max new tokens",
|
85 |
minimum=1,
|
@@ -118,11 +118,11 @@ chat_interface = gr.ChatInterface(
|
|
118 |
],
|
119 |
stop_btn=None,
|
120 |
examples=[
|
121 |
-
["
|
122 |
-
["
|
123 |
-
["
|
124 |
-
["
|
125 |
-
["
|
126 |
],
|
127 |
)
|
128 |
|
|
|
5 |
import gradio as gr
|
6 |
import spaces
|
7 |
import torch
|
8 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
|
9 |
|
10 |
MAX_MAX_NEW_TOKENS = 2048
|
11 |
DEFAULT_MAX_NEW_TOKENS = 1024
|
12 |
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
|
13 |
|
14 |
DESCRIPTION = """\
|
15 |
+
# ZhongJing-2-1_8b-merge
|
16 |
+
This Space demonstrates model [ZhongJing-2-1_8b-merge](https://huggingface.co/CMLL/ZhongJing-2-1_8b-merge) by CMLL, a powerful model for TCM-related applications. Feel free to play with it, or duplicate to run generations without a queue!
|
17 |
"""
|
18 |
|
19 |
LICENSE = """
|
20 |
<p/>
|
21 |
---
|
22 |
+
As a derivate work of [ZhongJing-2-1_8b-merge](https://huggingface.co/CMLL/ZhongJing-2-1_8b-merge) by CMLL,
|
23 |
+
this demo is governed by the original [license](https://huggingface.co/CMLL/ZhongJing-2-1_8b-merge/blob/main/LICENSE.txt) and [acceptable use policy](https://huggingface.co/CMLL/ZhongJing-2-1_8b-merge/blob/main/USE_POLICY.md).
|
24 |
"""
|
25 |
|
26 |
if not torch.cuda.is_available():
|
|
|
28 |
|
29 |
if torch.cuda.is_available():
|
30 |
model_id = "CMLL/ZhongJing-2-1_8b-merge"
|
31 |
+
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
|
32 |
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
33 |
tokenizer.use_default_system_prompt = False
|
34 |
|
|
|
36 |
def generate(
|
37 |
message: str,
|
38 |
chat_history: list[tuple[str, str]],
|
39 |
+
system_prompt: str,
|
40 |
max_new_tokens: int = 1024,
|
41 |
temperature: float = 0.6,
|
42 |
top_p: float = 0.9,
|
43 |
top_k: int = 50,
|
44 |
repetition_penalty: float = 1.2,
|
45 |
) -> Iterator[str]:
|
46 |
+
conversation = []
|
47 |
+
if system_prompt:
|
48 |
+
conversation.append({"role": "system", "content": system_prompt})
|
49 |
for user, assistant in chat_history:
|
50 |
conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
|
51 |
conversation.append({"role": "user", "content": message})
|
52 |
|
53 |
+
input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt")
|
54 |
+
if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
|
55 |
+
input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
|
56 |
+
gr.Warning(f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
|
57 |
+
input_ids = input_ids.to(model.device)
|
58 |
|
59 |
+
streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
|
60 |
+
generate_kwargs = dict(
|
61 |
+
{"input_ids": input_ids},
|
62 |
+
streamer=streamer,
|
63 |
+
max_new_tokens=max_new_tokens,
|
64 |
+
do_sample=True,
|
65 |
+
top_p=top_p,
|
66 |
+
top_k=top_k,
|
67 |
+
temperature=temperature,
|
68 |
+
num_beams=1,
|
69 |
+
repetition_penalty=repetition_penalty,
|
70 |
+
)
|
71 |
+
t = Thread(target=model.generate, kwargs=generate_kwargs)
|
72 |
+
t.start()
|
73 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
74 |
outputs = []
|
75 |
+
for text in streamer:
|
76 |
+
outputs.append(text)
|
77 |
+
yield "".join(outputs)
|
|
|
|
|
|
|
78 |
|
79 |
chat_interface = gr.ChatInterface(
|
80 |
fn=generate,
|
81 |
additional_inputs=[
|
82 |
+
gr.Textbox(label="System prompt", lines=6),
|
83 |
gr.Slider(
|
84 |
label="Max new tokens",
|
85 |
minimum=1,
|
|
|
118 |
],
|
119 |
stop_btn=None,
|
120 |
examples=[
|
121 |
+
["你是谁?"],
|
122 |
+
["你能简要解释一下什么是中医吗?"],
|
123 |
+
["简述《黄帝内经》的主要内容。"],
|
124 |
+
["中医如何治疗失眠?"],
|
125 |
+
["写一篇关于‘AI在中医研究中的应用’的100字文章。"],
|
126 |
],
|
127 |
)
|
128 |
|