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@@ -100,6 +100,7 @@ def get_download_links_from_huggingface(model, branch):
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links = []
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classifications = []
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has_pytorch = False
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+ has_pt = False
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has_safetensors = False
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is_lora = False
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while True:
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@@ -115,7 +116,7 @@ def get_download_links_from_huggingface(model, branch):
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is_lora = True
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is_pytorch = re.match("(pytorch|adapter)_model.*\.bin", fname)
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- is_safetensors = re.match("model.*\.safetensors", fname)
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+ is_safetensors = re.match(".*\.safetensors", fname)
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is_pt = re.match(".*\.pt", fname)
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is_tokenizer = re.match("tokenizer.*\.model", fname)
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is_text = re.match(".*\.(txt|json|py|md)", fname) or is_tokenizer
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@@ -134,6 +135,7 @@ def get_download_links_from_huggingface(model, branch):
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has_pytorch = True
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classifications.append('pytorch')
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elif is_pt:
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+ has_pt = True
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classifications.append('pt')
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cursor = base64.b64encode(f'{{"file_name":"{dict[-1]["path"]}"}}'.encode()) + b':50'
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@@ -141,9 +143,9 @@ def get_download_links_from_huggingface(model, branch):
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cursor = cursor.replace(b'=', b'%3D')
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# If both pytorch and safetensors are available, download safetensors only
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- if has_pytorch and has_safetensors:
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+ if (has_pytorch or has_pt) and has_safetensors:
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for i in range(len(classifications)-1, -1, -1):
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- if classifications[i] == 'pytorch':
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+ if classifications[i] in ['pytorch', 'pt']:
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links.pop(i)
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return links, is_lora
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