1094 lines
45 KiB
Plaintext
1094 lines
45 KiB
Plaintext
|
{
|
||
|
|
"cells": [
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 2,
|
||
|
|
"id": "070a4097-7a17-409f-af5d-3d0cf43926ca",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"from peft import AutoPeftModelForCausalLM, PeftModelForCausalLM\n",
|
||
|
|
"from huggingface_hub import list_repo_refs\n",
|
||
|
|
"from transformers import AutoTokenizer, AutoModelForCausalLM"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"id": "100ec138-f7c1-4d8f-b7e0-eb715f320fdc",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stderr",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokenizer = AutoTokenizer.from_pretrained(\"mnoukhov/pythia410m-tldr-sft\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"id": "dbc9a2db-2c16-4e8f-bd2a-213ddc5d139d",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"0"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokenizer.add_special_tokens({\"pad_token\": \"<|padding|>\"}) "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"id": "03788af8-6733-492f-84e3-fd358bb88ffd",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"1"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 16,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokenizer.pad_token_id"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"id": "576d3fda-7902-43d7-b4b1-3054f6192b11",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"example_text = \"hello my name is mr hello\""
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 24,
|
||
|
|
"id": "c73ddb0c-1551-4b12-82d8-26d3742d6f57",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"toks = tokenizer(example_text + tokenizer.eos_token, padding=\"max_length\", max_length=7, truncation=True)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"id": "8904af15-4d27-4718-b53a-060ae65173a9",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"{'input_ids': [25521, 619, 1416, 310, 278, 83, 23120], 'attention_mask': [1, 1, 1, 1, 1, 1, 1]}"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"toks"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 26,
|
||
|
|
"id": "8fcf7c83-e8df-457b-9eab-1b1ed2145a76",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"7"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 26,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sum(toks['attention_mask'])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 2,
|
||
|
|
"id": "ef1dddf6-1d26-4950-910a-c40b2cc394c6",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"base_model_name = \"vwxyzjn/EleutherAI_pythia-1b-deduped__sft__tldr\"\n",
|
||
|
|
"base_model_revision = \"sft__55513__1706646024\""
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 35,
|
||
|
|
"id": "bb0df32c-9d90-4ab0-a87d-0ff6ecab03b6",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"model_path = \"/home/toolkit/trl_results/mnoukhov/EleutherAI_pythia-1b-deduped__sft__tldr_dpo_costa_1b_fp16.yml_3d94f50_b9ff2_merged/main\""
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 36,
|
||
|
|
"id": "3ae77b2a-3132-4dd1-903b-35f28b7e7e5f",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"base_model = AutoModelForCausalLM.from_pretrained(model_path)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 37,
|
||
|
|
"id": "08c1d05d-44a4-4859-9d54-48e7a3cd1da7",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "12749e76749a40469d7732dc23e0f1dc",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"model.safetensors: 0%| | 0.00/4.05G [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"CommitInfo(commit_url='https://huggingface.co/mnoukhov/EleutherAI_pythia-1b-deduped__sft__tldr_dpo_costa_1b_fp16.yml_3d94f50_b9ff2_merged/commit/cd8f4bf53ab02881549cb73b6271005b2e8c3be6', commit_message='Upload GPTNeoXForCausalLM', commit_description='', oid='cd8f4bf53ab02881549cb73b6271005b2e8c3be6', pr_url=None, pr_revision=None, pr_num=None)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 37,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"base_model.push_to_hub(\"mnoukhov/EleutherAI_pythia-1b-deduped__sft__tldr_dpo_costa_1b_fp16.yml_3d94f50_b9ff2_merged\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"id": "9ef8927b-f908-460f-adba-54508b133ae0",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"adapter_repo = \"mnoukhov/EleutherAI_pythia-1b-deduped__sft__tldr_dpo_1b_fp16.yml_24e9f83\""
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"id": "cb7336d2-a4ac-4607-83ae-e7e1e0b1665d",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"refs = list_repo_refs(adapter_repo)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 6,
|
||
|
|
"id": "2ab002af-7f3b-41b1-a8ad-f7c2296bd68f",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "f4c8e90f4fba4589a00ec3ee75dc7505",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"adapter_config.json: 0%| | 0.00/706 [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "1eb21476d51f44858c32c59e72d70105",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"adapter_model.safetensors: 0%| | 0.00/18.5M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "014e10f937374412aa10524d1a4d7a8f",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"model.safetensors: 0%| | 0.00/4.05G [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"step2324\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "7c55865b8a7f4c6795b22c0a68b702a6",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"adapter_model.safetensors: 0%| | 0.00/18.5M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "58cb851b46974ae5a3cb066717520f8d",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"model.safetensors: 0%| | 0.00/4.05G [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"step1743\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "742410c4a20d4a09b10c0c96c8977df5",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"adapter_model.safetensors: 0%| | 0.00/18.5M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "48117e9ab89248038fa8a76ca9a191db",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"model.safetensors: 0%| | 0.00/4.05G [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"step1162\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "9b9cef19d78c465f900e345ac44acae6",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"adapter_model.safetensors: 0%| | 0.00/18.5M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "08878fc4eb1a407bb6238d4bec9e2817",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"model.safetensors: 0%| | 0.00/4.05G [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"step581\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "f39fc2322c504c4b9d6b601bbcbbb923",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"adapter_model.safetensors: 0%| | 0.00/18.5M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"step1\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"for branch in refs.branches:\n",
|
||
|
|
" if branch.name == \"main\":\n",
|
||
|
|
" continue\n",
|
||
|
|
"\n",
|
||
|
|
" model = PeftModelForCausalLM.from_pretrained(base_model, adapter_repo, revision=branch.name)\n",
|
||
|
|
" merged = model.merge_and_unload()\n",
|
||
|
|
" merged.push_to_hub(f\"{adapter_repo}_merged\", revision=branch.name)\n",
|
||
|
|
" print(branch.name)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 1,
|
||
|
|
"id": "24627996-2bc2-4944-a36c-0d86108a82c6",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"from datasets import load_dataset, builder, load_from_disk\n",
|
||
|
|
"builder.has_sufficient_disk_space = lambda needed_bytes, directory=\".\": True "
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"id": "ab8916ed-d39b-4d64-b287-ea4569567005",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"ds = load_from_disk(\"/home/toolkit/trl_results/vwxyzjn_summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1706381144/vwxyzjn_EleutherAI_pythia-1b-deduped__dpo__tldr\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"id": "6ee65d83-872d-4d96-9c81-be53f2fc54c1",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"'?'"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds['generations_dpo__55513__1707379566'][0][-1]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 13,
|
||
|
|
"id": "a11a3760-515b-4a02-9053-853aa3b06fd4",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"ppo_ds = load_from_disk(\"vwxyzjn_summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1706381144/vwxyzjn_EleutherAI_pythia-1b-deduped__ppo_left_padding_new_nowhiten_reward__tldr\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 24,
|
||
|
|
"id": "5d0c3c4f-71b1-46b0-abdb-036e1bd49a26",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"text = ppo_ds[\"generations_ppo_left_padding_new_nowhiten_reward__55513__1709671967\"][0]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 3,
|
||
|
|
"id": "8d2ec316-db2b-481b-9e25-82b2dd363772",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stderr",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokenizer = AutoTokenizer.from_pretrained(\"EleutherAI/pythia-6.9b-deduped\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 4,
|
||
|
|
"id": "1fedd4e0-a0a5-4499-9561-605e5adc8d88",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"[1]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 4,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokenizer.encode('<|padding|>')"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 5,
|
||
|
|
"id": "42b8260f-19a7-42e1-b809-a24deff3699c",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "032ad7febe1b4eb9899d22e5d44d23a0",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Downloading readme: 0%| | 0.00/456 [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "954fb6b000ac4b29b0c9033f242aac73",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Downloading data: 0%| | 0.00/122M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "3e544b20f15d48f59e901fbaf896a24d",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Downloading data: 0%| | 0.00/6.54M [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "62d3170267d742ceaf6bdad2a2cef5ae",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Generating train split: 0%| | 0/160800 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "ce7cff29f9c042949acad2dcec3ddd6e",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Generating test split: 0%| | 0/8552 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds = load_dataset(\"sophiex/hh-rlhf\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"id": "df1ccb5e-7206-45e7-a449-76b64fda72ed",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "a9abf38ffb184ba4a4995450a4413bf2",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map (num_proc=16): 0%| | 0/160800 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "8e0af258d31742998176207df5cac540",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map (num_proc=16): 0%| | 0/8552 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokds = ds.map(lambda x: tokenizer(x['prompt'] + x['chosen']), num_proc=16)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 12,
|
||
|
|
"id": "2e72f7f3-b047-4eab-99a7-cc08d19efeba",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "99c7615c05da46d6be5c68ecfba3e748",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map: 0%| | 0/160800 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "c9b61731ac524d8c8ad1a44e47bb12b2",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map: 0%| | 0/8552 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokds = tokds.map(lambda x: {\"length\": len(x['input_ids'])})"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 16,
|
||
|
|
"id": "413e3eb3-ad2f-4f71-9f27-894c4942be4f",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"import seaborn as sns"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"id": "a4c42a89-88dd-4f3d-82cb-1fd7ecb60815",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"<seaborn.axisgrid.FacetGrid at 0x7f8abec580d0>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 500x500 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"sns.displot(tokds[\"train\"][\"length\"])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 18,
|
||
|
|
"id": "d11597f9-0441-440c-8214-b9d8b2df6f79",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "46d3909d41c649acb800d4bf00197951",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map (num_proc=16): 0%| | 0/160800 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "e886faa17c774740a2058a5dd8e0673d",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map (num_proc=16): 0%| | 0/8552 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokds = ds.map(lambda x: tokenizer(x['prompt']), num_proc=16)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 19,
|
||
|
|
"id": "84290aac-1c4e-4d29-89bd-318cf2c9daf3",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "eb0406bdb9884fcc826630224f2d1a8a",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map: 0%| | 0/160800 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "50580c27e575445bb239783adee19f90",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Map: 0%| | 0/8552 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"tokds = tokds.map(lambda x: {\"prompt_length\": len(x['input_ids'])})"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"id": "44d2f307-118b-493d-b626-97490e2bc4aa",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "588d062fd6c2489da6f57b287c66d6e6",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Filter (num_proc=16): 0%| | 0/160800 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "bc9327dc6ed2467597a56b4655aca9a9",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Filter (num_proc=16): 0%| | 0/8552 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"filttokds = tokds.filter(lambda x: x[\"prompt_length\"] > 1024, num_proc=16)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 25,
|
||
|
|
"id": "2b6d57f7-40b7-4417-88bc-83c63b22f153",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"31"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 25,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"len(filttokds[\"test\"])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"id": "78d391fa-9a57-446b-9007-fe64ef8fc735",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"tokds = ds.map(lambda x: tokenizer(x['prompt']), num_proc=16)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 31,
|
||
|
|
"id": "176dbd05-67c5-45a6-b891-1237deb7d6c9",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"ds = load_dataset(\"mnoukhov/summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1706381144\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 32,
|
||
|
|
"id": "9eab3eaa-55ed-4279-96d6-3c189266ba86",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "911df020ac294d9ca2b360e1a0be3f93",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Filter: 0%| | 0/116722 [00:00<?, ? examples/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds[\"train\"] = ds[\"train\"].filter(lambda x: x[\"has_comparison\"] == True)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 34,
|
||
|
|
"id": "9cc44838-af6d-4e3d-be4e-49436900f469",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "4041ceb7527a4e638b138fc12897c35e",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Uploading the dataset shards: 0%| | 0/1 [00:00<?, ?it/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "51b19ac739f14b31a5820a9f077cf177",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Creating parquet from Arrow format: 0%| | 0/10 [00:00<?, ?ba/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "d7e0c946845940bb8de920287d982cd6",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Uploading the dataset shards: 0%| | 0/1 [00:00<?, ?it/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "acd8997214f448ca8cc665b4fd3b1af6",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Creating parquet from Arrow format: 0%| | 0/7 [00:00<?, ?ba/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "cae753400174470f8c97d61fbb557202",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Uploading the dataset shards: 0%| | 0/1 [00:00<?, ?it/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "2e6161edbdc24eca8fc89781a3b511e8",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"Creating parquet from Arrow format: 0%| | 0/7 [00:00<?, ?ba/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"name": "stderr",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"/home/toolkit/.local/lib/python3.11/site-packages/huggingface_hub/file_download.py:983: UserWarning: Not enough free disk space to download the file. The expected file size is: 0.00 MB. The target location /home/toolkit/huggingface/hub only has 0.00 MB free disk space.\n",
|
||
|
|
" warnings.warn(\n",
|
||
|
|
"/home/toolkit/.local/lib/python3.11/site-packages/huggingface_hub/file_download.py:983: UserWarning: Not enough free disk space to download the file. The expected file size is: 0.00 MB. The target location /home/toolkit/huggingface/hub/datasets--mnoukhov--summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1706381144_labelled/blobs only has 0.00 MB free disk space.\n",
|
||
|
|
" warnings.warn(\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"application/vnd.jupyter.widget-view+json": {
|
||
|
|
"model_id": "d6504b2578bf42a3810c24e04da166e1",
|
||
|
|
"version_major": 2,
|
||
|
|
"version_minor": 0
|
||
|
|
},
|
||
|
|
"text/plain": [
|
||
|
|
"README.md: 0%| | 0.00/1.17k [00:00<?, ?B/s]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"CommitInfo(commit_url='https://huggingface.co/datasets/mnoukhov/summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1706381144_labelled/commit/a873a0b902f97283fb440254b724da8257439c33', commit_message='Upload dataset', commit_description='', oid='a873a0b902f97283fb440254b724da8257439c33', pr_url=None, pr_revision=None, pr_num=None)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 34,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds.push_to_hub(\"mnoukhov/summarize_from_feedback_tldr_3_filtered_oai_preprocessing_1706381144_labelled\")"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 33,
|
||
|
|
"id": "557d07cf-781c-4c9a-8499-2bd4d076e98d",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"DatasetDict({\n",
|
||
|
|
" train: Dataset({\n",
|
||
|
|
" features: ['id', 'subreddit', 'title', 'post', 'summary', 'query_token', 'query', 'reference_response', 'reference_response_token', 'reference_response_token_len', 'query_reference_response', 'query_reference_response_token', 'query_reference_response_token_response_label', 'query_reference_response_token_len', 'has_comparison'],\n",
|
||
|
|
" num_rows: 9504\n",
|
||
|
|
" })\n",
|
||
|
|
" validation: Dataset({\n",
|
||
|
|
" features: ['id', 'subreddit', 'title', 'post', 'summary', 'query_token', 'query', 'reference_response', 'reference_response_token', 'reference_response_token_len', 'query_reference_response', 'query_reference_response_token', 'query_reference_response_token_response_label', 'query_reference_response_token_len', 'has_comparison'],\n",
|
||
|
|
" num_rows: 6447\n",
|
||
|
|
" })\n",
|
||
|
|
" test: Dataset({\n",
|
||
|
|
" features: ['id', 'subreddit', 'title', 'post', 'summary', 'query_token', 'query', 'reference_response', 'reference_response_token', 'reference_response_token_len', 'query_reference_response', 'query_reference_response_token', 'query_reference_response_token_response_label', 'query_reference_response_token_len', 'has_comparison'],\n",
|
||
|
|
" num_rows: 6553\n",
|
||
|
|
" })\n",
|
||
|
|
"})"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 33,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"ds"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"id": "a7ad1cea-5ac6-4d57-9aff-6783ea61fb13",
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3 (ipykernel)",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.11.2"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 5
|
||
|
|
}
|