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Eagle-X5-13B-Chat

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Error in gradio when running locally

Traceback (most recent call last):
  File "C:\Python310\lib\threading.py", line 1016, in _bootstrap_inner
    self.run()
  File "C:\Python310\lib\threading.py", line 953, in run
    self._target(*self._args, **self._kwargs)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\eagle\model\language_model\eagle_llama.py", line 139, in generate
    ) = self.prepare_inputs_labels_for_multimodal(
  File "C:\AI\!Training\EAGLE\eagle\model\eagle_arch.py", line 221, in prepare_inputs_labels_for_multimodal
    image_features = self.encode_images(images)
  File "C:\AI\!Training\EAGLE\eagle\model\eagle_arch.py", line 160, in encode_images
    image_features = self.get_model().get_vision_tower()(images)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\eagle\model\multimodal_encoder\multi_backbone_channel_concatenation_encoder.py", line 116, in forward
    feature = vision_tower(resized_x)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\eagle\model\multimodal_encoder\hr_clip_encoder.py", line 126, in forward
    x = self.vision_tower.vision_model.embeddings(x)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\eagle\model\multimodal_encoder\hr_clip_encoder.py", line 34, in forward_embeddings
    patch_embeds = self.patch_embedding(pixel_values.to(dtype=target_dtype))  # shape = [*, width, grid, grid]
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\conv.py", line 460, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\torch\nn\modules\conv.py", line 456, in _conv_forward
    return F.conv2d(input, weight, bias, self.stride,
RuntimeError: "slow_conv2d_cpu" not implemented for 'Half'
Traceback (most recent call last):
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\queueing.py", line 495, in call_prediction
    output = await route_utils.call_process_api(
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\route_utils.py", line 232, in call_process_api
    output = await app.get_blocks().process_api(
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\blocks.py", line 1561, in process_api
    result = await self.call_function(
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\blocks.py", line 1191, in call_function
    prediction = await utils.async_iteration(iterator)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\utils.py", line 521, in async_iteration
    return await iterator.__anext__()
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\utils.py", line 514, in __anext__
    return await anyio.to_thread.run_sync(
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\anyio\to_thread.py", line 56, in run_sync
    return await get_async_backend().run_sync_in_worker_thread(
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 2177, in run_sync_in_worker_thread
    return await future
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 859, in run
    result = context.run(func, *args)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\utils.py", line 497, in run_sync_iterator_async
    return next(iterator)
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\gradio\utils.py", line 678, in gen_wrapper
    response = next(iterator)
  File "C:\AI\!Training\EAGLE\gradio_demo.py", line 169, in generate
    for new_text in streamer:
  File "C:\AI\!Training\EAGLE\venv\lib\site-packages\transformers\generation\streamers.py", line 223, in __next__
    value = self.text_queue.get(timeout=self.timeout)
  File "C:\Python310\lib\queue.py", line 179, in get
    raise Empty
_queue.Empty

Any suggestions?