seed-data
Browse files- notebooks/.ipynb_checkpoints/convert-lm-eval-harness-checkpoint.ipynb +8 -8
- notebooks/convert-lm-eval-harness.ipynb +8 -8
- seed_data/arc_challenge.jsonl +3 -0
- seed_data/arc_easy.jsonl +3 -0
- seed_data/boolq.jsonl +3 -0
- seed_data/copa.jsonl +3 -0
- seed_data/hellaswag.jsonl +3 -0
- seed_data/piqa.jsonl +3 -0
- seed_data/winogrande.jsonl +3 -0
notebooks/.ipynb_checkpoints/convert-lm-eval-harness-checkpoint.ipynb
CHANGED
@@ -39,7 +39,7 @@
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|
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"task_name = 'hellaswag'\n",
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40 |
"data = load_dataset(task_name)\n",
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"data.shuffle(seed=42)\n",
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-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
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43 |
" for i_item, item in enumerate(data['train']):\n",
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" text = item['ctx'] + item['endings'][int(item['label'])]\n",
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" f.write(\n",
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@@ -117,7 +117,7 @@
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"task_name = 'boolq'\n",
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"data = load_dataset(task_name)\n",
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"data.shuffle(seed=42)\n",
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120 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
121 |
" for i_item, item in enumerate(data['train']):\n",
|
122 |
" text = f\"{item['passage']}\\nQuestion: {item['question']}?\\nAnswer: {item['answer']}\"\n",
|
123 |
" f.write(\n",
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@@ -144,7 +144,7 @@
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"task_name = 'arc_challenge'\n",
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"data = load_dataset('ai2_arc', 'ARC-Challenge')\n",
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146 |
"data.shuffle(seed=42)\n",
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147 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
148 |
" for i_item, item in enumerate(data['train']):\n",
|
149 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
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150 |
" q = item['question']\n",
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@@ -174,7 +174,7 @@
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"task_name = 'arc_easy'\n",
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"data = load_dataset('ai2_arc', 'ARC-Easy')\n",
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"data.shuffle(seed=42)\n",
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177 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
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178 |
" for i_item, item in enumerate(data['train']):\n",
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179 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
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" q = item['question']\n",
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@@ -207,7 +207,7 @@
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"task_name = 'copa'\n",
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"data = load_dataset('super_glue', task_name)\n",
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"data.shuffle(seed=42)\n",
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-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
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211 |
" for i_item, item in enumerate(data['train']):\n",
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" i_a = item['label']\n",
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" premise = item['premise']\n",
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@@ -248,7 +248,7 @@
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"task_name = 'piqa'\n",
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"data = load_dataset(task_name)\n",
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"data.shuffle(seed=42)\n",
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251 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
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252 |
" for i_item, item in enumerate(data['train']):\n",
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" i_a = item['label']\n",
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254 |
" goal = item['goal']\n",
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@@ -282,7 +282,7 @@
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"task_name = 'winogrande'\n",
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"data = load_dataset(task_name, 'winogrande_xl')\n",
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"data.shuffle(seed=42)\n",
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285 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
286 |
" for i_item, item in enumerate(data['train']):\n",
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" i_a = item['answer']\n",
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" sentence = item['sentence']\n",
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@@ -309,7 +309,7 @@
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}
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],
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"source": [
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-
"dataset = load_dataset(\"juewang/target-data\", data_files='
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]
|
314 |
},
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{
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"task_name = 'hellaswag'\n",
|
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"data = load_dataset(task_name)\n",
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41 |
"data.shuffle(seed=42)\n",
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+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
43 |
" for i_item, item in enumerate(data['train']):\n",
|
44 |
" text = item['ctx'] + item['endings'][int(item['label'])]\n",
|
45 |
" f.write(\n",
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|
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"task_name = 'boolq'\n",
|
118 |
"data = load_dataset(task_name)\n",
|
119 |
"data.shuffle(seed=42)\n",
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120 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
121 |
" for i_item, item in enumerate(data['train']):\n",
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122 |
" text = f\"{item['passage']}\\nQuestion: {item['question']}?\\nAnswer: {item['answer']}\"\n",
|
123 |
" f.write(\n",
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|
144 |
"task_name = 'arc_challenge'\n",
|
145 |
"data = load_dataset('ai2_arc', 'ARC-Challenge')\n",
|
146 |
"data.shuffle(seed=42)\n",
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147 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
148 |
" for i_item, item in enumerate(data['train']):\n",
|
149 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
|
150 |
" q = item['question']\n",
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|
174 |
"task_name = 'arc_easy'\n",
|
175 |
"data = load_dataset('ai2_arc', 'ARC-Easy')\n",
|
176 |
"data.shuffle(seed=42)\n",
|
177 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
178 |
" for i_item, item in enumerate(data['train']):\n",
|
179 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
|
180 |
" q = item['question']\n",
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|
207 |
"task_name = 'copa'\n",
|
208 |
"data = load_dataset('super_glue', task_name)\n",
|
209 |
"data.shuffle(seed=42)\n",
|
210 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
211 |
" for i_item, item in enumerate(data['train']):\n",
|
212 |
" i_a = item['label']\n",
|
213 |
" premise = item['premise']\n",
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|
|
248 |
"task_name = 'piqa'\n",
|
249 |
"data = load_dataset(task_name)\n",
|
250 |
"data.shuffle(seed=42)\n",
|
251 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
252 |
" for i_item, item in enumerate(data['train']):\n",
|
253 |
" i_a = item['label']\n",
|
254 |
" goal = item['goal']\n",
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|
282 |
"task_name = 'winogrande'\n",
|
283 |
"data = load_dataset(task_name, 'winogrande_xl')\n",
|
284 |
"data.shuffle(seed=42)\n",
|
285 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
286 |
" for i_item, item in enumerate(data['train']):\n",
|
287 |
" i_a = item['answer']\n",
|
288 |
" sentence = item['sentence']\n",
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|
|
309 |
}
|
310 |
],
|
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"source": [
|
312 |
+
"dataset = load_dataset(\"juewang/target-data\", data_files='seed_data/*.jsonl', split='train')"
|
313 |
]
|
314 |
},
|
315 |
{
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notebooks/convert-lm-eval-harness.ipynb
CHANGED
@@ -39,7 +39,7 @@
|
|
39 |
"task_name = 'hellaswag'\n",
|
40 |
"data = load_dataset(task_name)\n",
|
41 |
"data.shuffle(seed=42)\n",
|
42 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
43 |
" for i_item, item in enumerate(data['train']):\n",
|
44 |
" text = item['ctx'] + item['endings'][int(item['label'])]\n",
|
45 |
" f.write(\n",
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@@ -117,7 +117,7 @@
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|
117 |
"task_name = 'boolq'\n",
|
118 |
"data = load_dataset(task_name)\n",
|
119 |
"data.shuffle(seed=42)\n",
|
120 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
121 |
" for i_item, item in enumerate(data['train']):\n",
|
122 |
" text = f\"{item['passage']}\\nQuestion: {item['question']}?\\nAnswer: {item['answer']}\"\n",
|
123 |
" f.write(\n",
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@@ -144,7 +144,7 @@
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|
144 |
"task_name = 'arc_challenge'\n",
|
145 |
"data = load_dataset('ai2_arc', 'ARC-Challenge')\n",
|
146 |
"data.shuffle(seed=42)\n",
|
147 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
148 |
" for i_item, item in enumerate(data['train']):\n",
|
149 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
|
150 |
" q = item['question']\n",
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@@ -174,7 +174,7 @@
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|
174 |
"task_name = 'arc_easy'\n",
|
175 |
"data = load_dataset('ai2_arc', 'ARC-Easy')\n",
|
176 |
"data.shuffle(seed=42)\n",
|
177 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
178 |
" for i_item, item in enumerate(data['train']):\n",
|
179 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
|
180 |
" q = item['question']\n",
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@@ -207,7 +207,7 @@
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|
207 |
"task_name = 'copa'\n",
|
208 |
"data = load_dataset('super_glue', task_name)\n",
|
209 |
"data.shuffle(seed=42)\n",
|
210 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
211 |
" for i_item, item in enumerate(data['train']):\n",
|
212 |
" i_a = item['label']\n",
|
213 |
" premise = item['premise']\n",
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@@ -248,7 +248,7 @@
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|
248 |
"task_name = 'piqa'\n",
|
249 |
"data = load_dataset(task_name)\n",
|
250 |
"data.shuffle(seed=42)\n",
|
251 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
252 |
" for i_item, item in enumerate(data['train']):\n",
|
253 |
" i_a = item['label']\n",
|
254 |
" goal = item['goal']\n",
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@@ -282,7 +282,7 @@
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282 |
"task_name = 'winogrande'\n",
|
283 |
"data = load_dataset(task_name, 'winogrande_xl')\n",
|
284 |
"data.shuffle(seed=42)\n",
|
285 |
-
"with open(f'../{task_name}.jsonl', 'w') as f:\n",
|
286 |
" for i_item, item in enumerate(data['train']):\n",
|
287 |
" i_a = item['answer']\n",
|
288 |
" sentence = item['sentence']\n",
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@@ -309,7 +309,7 @@
|
|
309 |
}
|
310 |
],
|
311 |
"source": [
|
312 |
-
"dataset = load_dataset(\"juewang/target-data\", data_files='
|
313 |
]
|
314 |
},
|
315 |
{
|
|
|
39 |
"task_name = 'hellaswag'\n",
|
40 |
"data = load_dataset(task_name)\n",
|
41 |
"data.shuffle(seed=42)\n",
|
42 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
43 |
" for i_item, item in enumerate(data['train']):\n",
|
44 |
" text = item['ctx'] + item['endings'][int(item['label'])]\n",
|
45 |
" f.write(\n",
|
|
|
117 |
"task_name = 'boolq'\n",
|
118 |
"data = load_dataset(task_name)\n",
|
119 |
"data.shuffle(seed=42)\n",
|
120 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
121 |
" for i_item, item in enumerate(data['train']):\n",
|
122 |
" text = f\"{item['passage']}\\nQuestion: {item['question']}?\\nAnswer: {item['answer']}\"\n",
|
123 |
" f.write(\n",
|
|
|
144 |
"task_name = 'arc_challenge'\n",
|
145 |
"data = load_dataset('ai2_arc', 'ARC-Challenge')\n",
|
146 |
"data.shuffle(seed=42)\n",
|
147 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
148 |
" for i_item, item in enumerate(data['train']):\n",
|
149 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
|
150 |
" q = item['question']\n",
|
|
|
174 |
"task_name = 'arc_easy'\n",
|
175 |
"data = load_dataset('ai2_arc', 'ARC-Easy')\n",
|
176 |
"data.shuffle(seed=42)\n",
|
177 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
178 |
" for i_item, item in enumerate(data['train']):\n",
|
179 |
" i_a = item['choices']['label'].index(item['answerKey'])\n",
|
180 |
" q = item['question']\n",
|
|
|
207 |
"task_name = 'copa'\n",
|
208 |
"data = load_dataset('super_glue', task_name)\n",
|
209 |
"data.shuffle(seed=42)\n",
|
210 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
211 |
" for i_item, item in enumerate(data['train']):\n",
|
212 |
" i_a = item['label']\n",
|
213 |
" premise = item['premise']\n",
|
|
|
248 |
"task_name = 'piqa'\n",
|
249 |
"data = load_dataset(task_name)\n",
|
250 |
"data.shuffle(seed=42)\n",
|
251 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
252 |
" for i_item, item in enumerate(data['train']):\n",
|
253 |
" i_a = item['label']\n",
|
254 |
" goal = item['goal']\n",
|
|
|
282 |
"task_name = 'winogrande'\n",
|
283 |
"data = load_dataset(task_name, 'winogrande_xl')\n",
|
284 |
"data.shuffle(seed=42)\n",
|
285 |
+
"with open(f'../seed_data{task_name}.jsonl', 'w') as f:\n",
|
286 |
" for i_item, item in enumerate(data['train']):\n",
|
287 |
" i_a = item['answer']\n",
|
288 |
" sentence = item['sentence']\n",
|
|
|
309 |
}
|
310 |
],
|
311 |
"source": [
|
312 |
+
"dataset = load_dataset(\"juewang/target-data\", data_files='seed_data/*.jsonl', split='train')"
|
313 |
]
|
314 |
},
|
315 |
{
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seed_data/arc_challenge.jsonl
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2d64da34cc4eb901214d1c4317a73579c31d0d82d2cfca7d62ceff07f51e2e9c
|
3 |
+
size 240469
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seed_data/arc_easy.jsonl
ADDED
@@ -0,0 +1,3 @@
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|
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|
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1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:376d29e4f199c6899ec3ea22f34f35e62a4b59dbf722d194b02f151b2dca7293
|
3 |
+
size 423646
|
seed_data/boolq.jsonl
ADDED
@@ -0,0 +1,3 @@
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|
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|
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|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8a3f37660a3909415cdeb102c2dbe06187d607fe7e49bd6a6129bb6dfa5bdc3a
|
3 |
+
size 6332634
|
seed_data/copa.jsonl
ADDED
@@ -0,0 +1,3 @@
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|
|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:261a8413a7fa5af6b129dee1c435976f4c7086187c5ea3dd5fd14939ee14bb92
|
3 |
+
size 40851
|
seed_data/hellaswag.jsonl
ADDED
@@ -0,0 +1,3 @@
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|
|
|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2dc59132b7c9ed7513eb428d8bde1f5214c24aaa196a404c05acee36cc5c9838
|
3 |
+
size 15630002
|
seed_data/piqa.jsonl
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:68f23de850360818d0e3733f9fe1540929a9de22e53d25145d831c5932ad520b
|
3 |
+
size 3003394
|
seed_data/winogrande.jsonl
ADDED
@@ -0,0 +1,3 @@
|
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|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ac8f07178644445f6421314b899ff976f49c25804d43cd163734cf139f380681
|
3 |
+
size 5711173
|