abetlen commited on
Commit
12eb8ec
·
1 Parent(s): 4d699b1
Files changed (3) hide show
  1. app.py +3 -4
  2. gradio_helpers.py +4 -5
  3. models.py +2 -3
app.py CHANGED
@@ -161,7 +161,7 @@ def create_app():
161
  gr.on(
162
  [run.click, prompt.submit],
163
  compute,
164
- [image, prompt, model + "-text-model-q4_k_m.gguf", sampler],
165
  [highlighted_text, image, annotated_image],
166
  )
167
  clear.click(
@@ -244,8 +244,7 @@ if __name__ == '__main__':
244
  logging.info('environ["%s"] = %r', k, v)
245
 
246
  gradio_helpers.set_warmup_function(warmup)
247
- for name, (repo, filename) in models.MODELS.items():
248
- gradio_helpers.register_download(name + "-text-model-q4_k_m.gguf", repo, filename + "-text-model-q4_k_m.gguf")
249
- gradio_helpers.register_download(name + "-mmproj-f16.gguf", repo, filename + "-mmproj-f16.gguf")
250
 
251
  create_app().queue().launch()
 
161
  gr.on(
162
  [run.click, prompt.submit],
163
  compute,
164
+ [image, prompt, model, sampler],
165
  [highlighted_text, image, annotated_image],
166
  )
167
  clear.click(
 
244
  logging.info('environ["%s"] = %r', k, v)
245
 
246
  gradio_helpers.set_warmup_function(warmup)
247
+ for name, (repo, filenames) in models.MODELS.items():
248
+ gradio_helpers.register_download(name, repo, filenames)
 
249
 
250
  create_app().queue().launch()
gradio_helpers.py CHANGED
@@ -74,7 +74,7 @@ def _do_download():
74
  time.sleep(1)
75
  continue
76
 
77
- name, (repo, filename, revision) = next(iter(_scheduled.items()))
78
  logging.info('Downloading "%s" %s/%s/%s...', name, repo, filename, revision)
79
  with timed(f'downloading {name}', True) as t:
80
  if should_mock():
@@ -83,8 +83,7 @@ def _do_download():
83
  _done[name] = None
84
  else:
85
  try:
86
- _done[name] = huggingface_hub.hf_hub_download(
87
- repo_id=repo, filename=filename, revision=revision)
88
  except Exception as e: # pylint: disable=broad-exception-caught
89
  logging.exception('Could not download "%s" from hub!', name)
90
  _failed[name] = str(e)
@@ -109,11 +108,11 @@ def _do_download():
109
  _scheduled.pop(name)
110
 
111
 
112
- def register_download(name, repo, filename, revision='main'):
113
  """Will cause download of `filename` from HF `repo` in background thread."""
114
  with _lock:
115
  if name not in _scheduled:
116
- _scheduled[name] = (repo, filename, revision)
117
 
118
 
119
  def _hms(secs):
 
74
  time.sleep(1)
75
  continue
76
 
77
+ name, (repo, filenames, revision) = next(iter(_scheduled.items()))
78
  logging.info('Downloading "%s" %s/%s/%s...', name, repo, filename, revision)
79
  with timed(f'downloading {name}', True) as t:
80
  if should_mock():
 
83
  _done[name] = None
84
  else:
85
  try:
86
+ _done[name] = (huggingface_hub.hf_hub_download(repo_id=repo, filename=filename, revision=revision) for filename in filenames)
 
87
  except Exception as e: # pylint: disable=broad-exception-caught
88
  logging.exception('Could not download "%s" from hub!', name)
89
  _failed[name] = str(e)
 
108
  _scheduled.pop(name)
109
 
110
 
111
+ def register_download(name, repo, filenames, revision='main'):
112
  """Will cause download of `filename` from HF `repo` in background thread."""
113
  with _lock:
114
  if name not in _scheduled:
115
+ _scheduled[name] = (repo, filenames, revision)
116
 
117
 
118
  def _hms(secs):
models.py CHANGED
@@ -20,7 +20,7 @@ MODELS = {
20
  **{
21
  model_name: (
22
  f'{ORGANIZATION}/{repo}',
23
- f'{model_name}',
24
  )
25
  for repo, model_name in BASE_MODELS
26
  },
@@ -78,8 +78,7 @@ def generate(
78
  # with gradio_helpers.timed('computation', start_message=True):
79
  # tokens = model.predict(params, batch, sampler=sampler)
80
 
81
- model_path = gradio_helpers.get_paths()[model_name + "-text-model-q4_k_m.gguf"]
82
- clip_path = gradio_helpers.get_paths()[model_name + "-mmproj-f16.gguf"]
83
  print(model_path)
84
  print(gradio_helpers.get_paths())
85
  model = llama_cpp.Llama(
 
20
  **{
21
  model_name: (
22
  f'{ORGANIZATION}/{repo}',
23
+ (f'{model_name}-text-model-q4_k_m.gguf', f'{model_name}-mmproj-f16.gguf'),
24
  )
25
  for repo, model_name in BASE_MODELS
26
  },
 
78
  # with gradio_helpers.timed('computation', start_message=True):
79
  # tokens = model.predict(params, batch, sampler=sampler)
80
 
81
+ model_path, clip_path = gradio_helpers.get_paths()[model_name]
 
82
  print(model_path)
83
  print(gradio_helpers.get_paths())
84
  model = llama_cpp.Llama(