Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -32,23 +32,11 @@ available_models = ["0Tick/e621TagAutocomplete","0Tick/danbooruTagAutocomplete"]
|
|
32 |
current = Model()
|
33 |
job_count = 1
|
34 |
|
35 |
-
base_dir = scripts.basedir()
|
36 |
-
models_dir = os.path.join(base_dir, "models")
|
37 |
-
|
38 |
|
39 |
def device():
|
40 |
return devices.cpu
|
41 |
|
42 |
|
43 |
-
|
44 |
-
def get_model_path(name):
|
45 |
-
dirname = os.path.join(models_dir, name)
|
46 |
-
if not os.path.isdir(dirname):
|
47 |
-
return name
|
48 |
-
|
49 |
-
return dirname
|
50 |
-
|
51 |
-
|
52 |
def generate_batch(input_ids, min_length, max_length, num_beams, temperature, repetition_penalty, length_penalty, sampling_mode, top_k, top_p):
|
53 |
top_p = float(top_p) if sampling_mode == 'Top P' else None
|
54 |
top_k = int(top_k) if sampling_mode == 'Top K' else None
|
@@ -87,7 +75,7 @@ def generate(id_task, model_name, batch_count, batch_size, text, *args):
|
|
87 |
current.name = None
|
88 |
|
89 |
if model_name != 'None':
|
90 |
-
path =
|
91 |
current.tokenizer = transformers.AutoTokenizer.from_pretrained(path)
|
92 |
current.model = transformers.AutoModelForCausalLM.from_pretrained(path)
|
93 |
current.name = model_name
|
@@ -126,9 +114,6 @@ def generate(id_task, model_name, batch_count, batch_size, text, *args):
|
|
126 |
return markup, ''
|
127 |
|
128 |
|
129 |
-
|
130 |
-
list_available_models()
|
131 |
-
|
132 |
with gr.Blocks(analytics_enabled=False) as space:
|
133 |
with gr.Row():
|
134 |
with gr.Column(scale=80):
|
|
|
32 |
current = Model()
|
33 |
job_count = 1
|
34 |
|
|
|
|
|
|
|
35 |
|
36 |
def device():
|
37 |
return devices.cpu
|
38 |
|
39 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
40 |
def generate_batch(input_ids, min_length, max_length, num_beams, temperature, repetition_penalty, length_penalty, sampling_mode, top_k, top_p):
|
41 |
top_p = float(top_p) if sampling_mode == 'Top P' else None
|
42 |
top_k = int(top_k) if sampling_mode == 'Top K' else None
|
|
|
75 |
current.name = None
|
76 |
|
77 |
if model_name != 'None':
|
78 |
+
path = model_name
|
79 |
current.tokenizer = transformers.AutoTokenizer.from_pretrained(path)
|
80 |
current.model = transformers.AutoModelForCausalLM.from_pretrained(path)
|
81 |
current.name = model_name
|
|
|
114 |
return markup, ''
|
115 |
|
116 |
|
|
|
|
|
|
|
117 |
with gr.Blocks(analytics_enabled=False) as space:
|
118 |
with gr.Row():
|
119 |
with gr.Column(scale=80):
|