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import os
import sys
from tqdm import tqdm
import requests
if len(sys.argv) < 3:
print("Usage: download-pth.py dir-model model-type\n")
print(" model-type: Available models 7B, 13B, 30B or 65B")
sys.exit(1)
modelsDir = sys.argv[1]
model = sys.argv[2]
num = {
"7B": 1,
"13B": 2,
"30B": 4,
"65B": 8,
}
if model not in num:
print(f"Error: model {model} is not valid, provide 7B, 13B, 30B or 65B")
sys.exit(1)
print(f"Downloading model {model}")
files = ["checklist.chk", "params.json"]
for i in range(num[model]):
files.append(f"consolidated.0{i}.pth")
resolved_path = os.path.abspath(os.path.join(modelsDir, model))
os.makedirs(resolved_path, exist_ok=True)
for file in files:
dest_path = os.path.join(resolved_path, file)
if os.path.exists(dest_path):
print(f"Skip file download, it already exists: {file}")
continue
url = f"https://agi.gpt4.org/llama/LLaMA/{model}/{file}"
response = requests.get(url, stream=True)
with open(dest_path, 'wb') as f:
with tqdm(unit='B', unit_scale=True, miniters=1, desc=file) as t:
for chunk in response.iter_content(chunk_size=1024):
if chunk:
f.write(chunk)
t.update(len(chunk))
files2 = ["tokenizer_checklist.chk", "tokenizer.model"]
for file in files2:
dest_path = os.path.join(modelsDir, file)
if os.path.exists(dest_path):
print(f"Skip file download, it already exists: {file}")
continue
url = f"https://agi.gpt4.org/llama/LLaMA/{file}"
response = requests.get(url, stream=True)
with open(dest_path, 'wb') as f:
with tqdm(unit='B', unit_scale=True, miniters=1, desc=file) as t:
for chunk in response.iter_content(chunk_size=1024):
if chunk:
f.write(chunk)
t.update(len(chunk))
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