Duplicate from LLMs/Alpaca-ShareGPT

Co-authored-by: chansung park <chansung@users.noreply.huggingface.co>

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
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README.md

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+---
+license: apache-2.0
+---

convert-alpaca.py

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+import json
+
+alpaca_data = []
+filtered = 0
+processed_num = 0
+total_num = 0
+
+roles = set()
+
+raw_data = json.load(
+    open('ShareGPT_V3_unfiltered_cleaned_split.json')
+)
+
+for data in raw_data:
+    convs = data['conversations']
+    convs_len = len(convs)
+    total_num += convs_len
+
+    if convs_len > 0:
+        start_idx = 0 if convs[0]['from'] == "human" else 1
+        end_idx = convs_len if convs[convs_len-1]['from'] == "gpt" else convs_len-1
+
+        for idx in range(start_idx, end_idx, 2):
+            if idx+1 >= convs_len:
+                continue
+
+            human = convs[idx]
+            gpt = convs[idx+1]
+
+            if (human['from'] != 'human' and human['from'] != 'user') \
+                and (gpt['from'] != 'gpt' and gpt['from'] != 'bard' and gpt['from'] != 'chatgpt' and gpt['from'] != 'bing'):
+                continue
+
+            new_data = {
+                "instruction": human['value'],
+                "input": "",
+                "output": gpt['value']
+            }
+
+            alpaca_data.append(new_data)
+            processed_num += 2
+
+print(f"out of {total_num}, {processed_num} number of conversations are converted")
+print("save as JSON file...")
+
+json_obj = json.dumps(alpaca_data, indent=4)
+with open("alpaca_sharedgpt_data.json", "w") as outfile:
+    outfile.write(json_obj)
+print("DONE")