[tutorial] edited hands-on practices (#1899)

* Add handson to ColossalAI.

* Change names of handsons and edit sequence parallel example.

* Edit wrong folder name

* resolve conflict

* delete readme

examples/tutorial/opt/inference/script/processing_ckpt_66b.py

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+import os
+import torch
+from multiprocessing import Pool
+
+# download pytorch model ckpt in https://huggingface.co/facebook/opt-66b/tree/main
+# you can use whether wget or git lfs
+
+path = "/path/to/your/ckpt"
+new_path = "/path/to/the/processed/ckpt/"
+
+assert os.path.isdir(path)
+files = []
+for filename in os.listdir(path):
+    filepath = os.path.join(path, filename)
+    if os.path.isfile(filepath):
+        files.append(filepath)
+
+with Pool(14) as pool:
+    ckpts = pool.map(torch.load, files)
+
+restored = {}
+for ckpt in ckpts:
+    for k,v in ckpt.items():
+        if(k[0] == 'm'):
+            k = k[6:]      
+        if(k == "lm_head.weight"):
+            k = "head.dense.weight"
+        if(k == "decoder.final_layer_norm.weight"):
+            k = "decoder.layer_norm.weight"
+        if(k == "decoder.final_layer_norm.bias"):
+            k = "decoder.layer_norm.bias"
+        restored[k] = v
+restored["decoder.version"] = "0.0"
+
+
+split_num = len(restored.keys()) // 60
+count = 0
+file_count = 1
+tmp = {}
+for k,v in restored.items():
+    print(k)
+    tmp[k] = v
+    count = count + 1    
+    if(count == split_num):
+        filename = str(file_count) + "-restored.pt"
+        torch.save(tmp, os.path.join(new_path, filename))
+        file_count = file_count + 1
+        count = 0
+        tmp = {}
+
+filename = str(file_count) + "-restored.pt"
+torch.save(tmp, os.path.join(new_path, filename))
+
+
+