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hemantn commited on
Commit
bd0d9fa
·
1 Parent(s): 88ddbb1

updated notebook with updated adapter code

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Files changed (1) hide show
  1. test_ablang2_HF_implementation.ipynb +397 -35
test_ablang2_HF_implementation.ipynb CHANGED
@@ -11,6 +11,16 @@
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  {
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  "cell_type": "code",
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  "execution_count": 1,
 
 
 
 
 
 
 
 
 
 
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  "id": "7ae54cd0-6253-46dd-a316-4f20b12041e0",
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  "metadata": {},
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  "outputs": [],
@@ -40,7 +50,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 2,
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  "id": "99192978-a008-4a32-a80e-bba238e0ec7c",
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  "metadata": {},
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  "outputs": [],
@@ -82,14 +92,14 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 3,
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  "id": "6d66ad84",
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "application/vnd.jupyter.widget-view+json": {
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- "model_id": "a5acedae3cc4420ea2971400b0915426",
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  "version_major": 2,
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  "version_minor": 0
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  },
@@ -103,7 +113,7 @@
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  {
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  "data": {
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  "application/vnd.jupyter.widget-view+json": {
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- "model_id": "5727addb151447cf9bb091ef1159717c",
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  "version_major": 2,
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  "version_minor": 0
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  },
@@ -126,7 +136,7 @@
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  {
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  "data": {
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  "application/vnd.jupyter.widget-view+json": {
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- "model_id": "845b45d4aed542dc86ab7b7ac3305a0e",
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  "version_major": 2,
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  "version_minor": 0
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  },
@@ -141,22 +151,108 @@
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  "name": "stderr",
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  "output_type": "stream",
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  "text": [
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- "Encountered exception while importing ablang2: No module named 'ablang2'\n"
 
 
 
 
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  ]
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  },
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  {
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- "ename": "ImportError",
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- "evalue": "This modeling file requires the following packages that were not found in your environment: ablang2. Run `pip install ablang2`",
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- "output_type": "error",
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- "traceback": [
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- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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- "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)",
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- "Cell \u001b[0;32mIn[3], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# Load model and tokenizer from Hugging Face Hub\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhemantn/ablang2\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrust_remote_code\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m tokenizer \u001b[38;5;241m=\u001b[39m AutoTokenizer\u001b[38;5;241m.\u001b[39mfrom_pretrained(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhemantn/ablang2\u001b[39m\u001b[38;5;124m\"\u001b[39m, trust_remote_code\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m# Find the cached model directory and import adapter\u001b[39;00m\n",
155
- "File \u001b[0;32m~/.conda/envs/lib_transformer/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:582\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 579\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124madapter_kwargs\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m adapter_kwargs\n\u001b[1;32m 581\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m has_remote_code \u001b[38;5;129;01mand\u001b[39;00m trust_remote_code:\n\u001b[0;32m--> 582\u001b[0m model_class \u001b[38;5;241m=\u001b[39m \u001b[43mget_class_from_dynamic_module\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 583\u001b[0m \u001b[43m \u001b[49m\u001b[43mclass_ref\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcode_revision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcode_revision\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mhub_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m 584\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 585\u001b[0m _ \u001b[38;5;241m=\u001b[39m hub_kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcode_revision\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 586\u001b[0m \u001b[38;5;66;03m# This block handles the case where the user is loading a model with `trust_remote_code=True`\u001b[39;00m\n\u001b[1;32m 587\u001b[0m \u001b[38;5;66;03m# but a library model exists with the same name. We don't want to override the autoclass\u001b[39;00m\n\u001b[1;32m 588\u001b[0m \u001b[38;5;66;03m# mappings in this case, or all future loads of that model will be the remote code model.\u001b[39;00m\n",
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- "File \u001b[0;32m~/.conda/envs/lib_transformer/lib/python3.10/site-packages/transformers/dynamic_module_utils.py:570\u001b[0m, in \u001b[0;36mget_class_from_dynamic_module\u001b[0;34m(class_reference, pretrained_model_name_or_path, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, repo_type, code_revision, **kwargs)\u001b[0m\n\u001b[1;32m 568\u001b[0m code_revision \u001b[38;5;241m=\u001b[39m revision\n\u001b[1;32m 569\u001b[0m \u001b[38;5;66;03m# And lastly we get the class inside our newly created module\u001b[39;00m\n\u001b[0;32m--> 570\u001b[0m final_module \u001b[38;5;241m=\u001b[39m \u001b[43mget_cached_module_file\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 571\u001b[0m \u001b[43m \u001b[49m\u001b[43mrepo_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 572\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodule_file\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m.py\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 573\u001b[0m \u001b[43m \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 574\u001b[0m \u001b[43m \u001b[49m\u001b[43mforce_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 575\u001b[0m \u001b[43m \u001b[49m\u001b[43mresume_download\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mresume_download\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 576\u001b[0m \u001b[43m \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 577\u001b[0m \u001b[43m \u001b[49m\u001b[43mtoken\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtoken\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 578\u001b[0m \u001b[43m \u001b[49m\u001b[43mrevision\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcode_revision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 579\u001b[0m \u001b[43m \u001b[49m\u001b[43mlocal_files_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlocal_files_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 580\u001b[0m \u001b[43m \u001b[49m\u001b[43mrepo_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 581\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 582\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m get_class_in_module(class_name, final_module, force_reload\u001b[38;5;241m=\u001b[39mforce_download)\n",
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- "File \u001b[0;32m~/.conda/envs/lib_transformer/lib/python3.10/site-packages/transformers/dynamic_module_utils.py:393\u001b[0m, in \u001b[0;36mget_cached_module_file\u001b[0;34m(pretrained_model_name_or_path, module_file, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, repo_type, _commit_hash, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m 390\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[1;32m 392\u001b[0m \u001b[38;5;66;03m# Check we have all the requirements in our environment\u001b[39;00m\n\u001b[0;32m--> 393\u001b[0m modules_needed \u001b[38;5;241m=\u001b[39m \u001b[43mcheck_imports\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresolved_module_file\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 395\u001b[0m \u001b[38;5;66;03m# Now we move the module inside our cached dynamic modules.\u001b[39;00m\n\u001b[1;32m 396\u001b[0m full_submodule \u001b[38;5;241m=\u001b[39m TRANSFORMERS_DYNAMIC_MODULE_NAME \u001b[38;5;241m+\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39msep \u001b[38;5;241m+\u001b[39m submodule\n",
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- "File \u001b[0;32m~/.conda/envs/lib_transformer/lib/python3.10/site-packages/transformers/dynamic_module_utils.py:225\u001b[0m, in \u001b[0;36mcheck_imports\u001b[0;34m(filename)\u001b[0m\n\u001b[1;32m 222\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n\u001b[1;32m 224\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(missing_packages) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 225\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[1;32m 226\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThis modeling file requires the following packages that were not found in your environment: \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 227\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(missing_packages)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. Run `pip install \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(missing_packages)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m`\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 228\u001b[0m )\n\u001b[1;32m 230\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m get_relative_imports(filename)\n",
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- "\u001b[0;31mImportError\u001b[0m: This modeling file requires the following packages that were not found in your environment: ablang2. Run `pip install ablang2`"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ]
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  }
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  ],
@@ -205,7 +301,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "ceae4a88-0679-4704-8bad-c06a4569c497",
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  "metadata": {},
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  "outputs": [],
@@ -230,10 +326,30 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "d22f4302-1262-4cc1-8a1c-a36daa8c710c",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "ablang(all_seqs, mode='seqcoding')\n"
239
  ]
@@ -254,10 +370,85 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "6227f661-575f-4b1e-9646-cfba7b10c3b4",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "ablang(all_seqs, mode='rescoding', stepwise_masking = False)"
263
  ]
@@ -278,10 +469,80 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "e4bc0cb1-f5b0-4255-9e93-d643ae1396df",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "results = ablang(only_both_chains_seqs, mode='likelihood', align=True)\n",
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  "\n",
@@ -292,10 +553,60 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "56be8cad",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "ablang(only_both_chains_seqs, mode='probability')"
301
  ]
@@ -320,10 +631,21 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "83f3064b-48a7-42fb-ba82-ec153ea946da",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "results = ablang(all_seqs, mode='pseudo_log_likelihood')\n",
329
  "np.exp(-results) # convert to pseudo perplexity"
@@ -331,10 +653,22 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "42cc8b34-5ae9-4857-93fe-a438a0f2a868",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "results = ablang(all_seqs, mode='confidence')\n",
340
  "np.exp(-results)"
@@ -352,10 +686,24 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "2d5b725c-4eac-4a4b-9331-357c3ac140f7",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "restored = ablang(only_both_chains_seqs, mode='restore')\n",
361
  "restored"
@@ -363,10 +711,24 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "0e9615f7-c490-4947-96f4-7617266c686e",
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  "metadata": {},
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- "outputs": [],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "source": [
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  "restored = ablang(only_both_chains_seqs, mode='restore', align = True)\n",
372
  "restored"
 
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  {
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  "cell_type": "code",
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  "execution_count": 1,
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+ "id": "a51e7ed2",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "!rm -rf ~/.cache/huggingface/hub/models--hemantn--ablang2"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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  "id": "7ae54cd0-6253-46dd-a316-4f20b12041e0",
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  "metadata": {},
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  "outputs": [],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 3,
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  "id": "99192978-a008-4a32-a80e-bba238e0ec7c",
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  "metadata": {},
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  "outputs": [],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 4,
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  "id": "6d66ad84",
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  "metadata": {},
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  "outputs": [
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  {
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  "data": {
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  "application/vnd.jupyter.widget-view+json": {
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+ "model_id": "faac2d2a21ea4775b88db5f4af82a16a",
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  "version_major": 2,
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  "version_minor": 0
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  },
 
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  "data": {
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  "application/vnd.jupyter.widget-view+json": {
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+ "model_id": "6b4ea4ff07cb443cb4a6ac72e23faab9",
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  "version_major": 2,
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  "version_minor": 0
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  },
 
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  {
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  "data": {
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  "application/vnd.jupyter.widget-view+json": {
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+ "model_id": "23a70f36648e4242bb32595ab85a7c36",
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  "version_major": 2,
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  "version_minor": 0
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  },
 
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  "name": "stderr",
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  "text": [
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155
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156
+ ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n",
157
+ "/home/hn533621/.conda/envs/lib_transformer/lib/python3.10/site-packages/huggingface_hub/file_download.py:943: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
158
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159
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160
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201
+ "- tokenizer_ablang2paired.py\n",
202
+ ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
203
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204
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+ "name": "stdout",
235
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237
+ "✅ Copied restoration.py to current directory\n",
238
+ "✅ Copied ablang_encodings.py to current directory\n",
239
+ "✅ Copied alignment.py to current directory\n",
240
+ "✅ Copied scores.py to current directory\n",
241
+ "✅ Copied extra_utils.py to current directory\n",
242
+ "✅ Copied ablang.py to current directory\n",
243
+ "✅ Copied encoderblock.py to current directory\n",
244
+ "📁 Files in current directory (/home/hn533621/.cache/huggingface/hub/models--hemantn--ablang2/snapshots/88ddbb1fcb11297c3fd439b83500743e6adc25c0):\n",
245
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253
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256
  ]
257
  }
258
  ],
 
301
  },
302
  {
303
  "cell_type": "code",
304
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305
  "id": "ceae4a88-0679-4704-8bad-c06a4569c497",
306
  "metadata": {},
307
  "outputs": [],
 
326
  },
327
  {
328
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  "id": "d22f4302-1262-4cc1-8a1c-a36daa8c710c",
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  "source": [
354
  "ablang(all_seqs, mode='seqcoding')\n"
355
  ]
 
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372
  "cell_type": "code",
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  "source": [
453
  "ablang(all_seqs, mode='rescoding', stepwise_masking = False)"
454
  ]
 
469
  },
470
  {
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  "cell_type": "code",
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+ "execution_count": 8,
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  "id": "e4bc0cb1-f5b0-4255-9e93-d643ae1396df",
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  "metadata": {},
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497
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542
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543
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544
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545
+ ],
546
  "source": [
547
  "results = ablang(only_both_chains_seqs, mode='likelihood', align=True)\n",
548
  "\n",
 
553
  },
554
  {
555
  "cell_type": "code",
556
+ "execution_count": 9,
557
  "id": "56be8cad",
558
  "metadata": {},
559
+ "outputs": [
560
+ {
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+ "data": {
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565
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566
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567
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570
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573
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574
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582
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586
+ " 1.8233513e-07, 2.4615032e-08],\n",
587
+ " [7.3952030e-04, 2.8970928e-05, 8.7113440e-06, ..., 6.7168833e-11,\n",
588
+ " 1.3746008e-07, 1.0210846e-04]], shape=(222, 26), dtype=float32),\n",
589
+ " array([[9.99685407e-01, 3.35662639e-06, 1.14241482e-06, ...,\n",
590
+ " 2.32460891e-11, 6.88188067e-08, 5.69467156e-05],\n",
591
+ " [6.38133372e-07, 1.01300586e-07, 5.64459742e-06, ...,\n",
592
+ " 4.09234556e-11, 2.53804799e-09, 4.31722100e-07],\n",
593
+ " [1.49096788e-08, 2.04515047e-04, 9.23794141e-06, ...,\n",
594
+ " 7.46306961e-10, 2.92107380e-11, 2.21786500e-08],\n",
595
+ " ...,\n",
596
+ " [2.15093763e-07, 1.06453872e-03, 1.62486140e-05, ...,\n",
597
+ " 1.12102910e-10, 1.47300866e-10, 4.73037538e-08],\n",
598
+ " [4.30136682e-09, 3.09317988e-06, 3.96632568e-05, ...,\n",
599
+ " 5.24226877e-11, 2.39579450e-08, 3.86403221e-09],\n",
600
+ " [9.77773685e-04, 1.29533228e-05, 2.78623725e-06, ...,\n",
601
+ " 2.73364300e-11, 3.96418649e-08, 4.04014427e-05]],\n",
602
+ " shape=(238, 26), dtype=float32)]"
603
+ ]
604
+ },
605
+ "execution_count": 9,
606
+ "metadata": {},
607
+ "output_type": "execute_result"
608
+ }
609
+ ],
610
  "source": [
611
  "ablang(only_both_chains_seqs, mode='probability')"
612
  ]
 
631
  },
632
  {
633
  "cell_type": "code",
634
+ "execution_count": 10,
635
  "id": "83f3064b-48a7-42fb-ba82-ec153ea946da",
636
  "metadata": {},
637
+ "outputs": [
638
+ {
639
+ "data": {
640
+ "text/plain": [
641
+ "array([1.96673731, 2.04801253, 2.09881898, 1.82533665, 1.97255249])"
642
+ ]
643
+ },
644
+ "execution_count": 10,
645
+ "metadata": {},
646
+ "output_type": "execute_result"
647
+ }
648
+ ],
649
  "source": [
650
  "results = ablang(all_seqs, mode='pseudo_log_likelihood')\n",
651
  "np.exp(-results) # convert to pseudo perplexity"
 
653
  },
654
  {
655
  "cell_type": "code",
656
+ "execution_count": 11,
657
  "id": "42cc8b34-5ae9-4857-93fe-a438a0f2a868",
658
  "metadata": {},
659
+ "outputs": [
660
+ {
661
+ "data": {
662
+ "text/plain": [
663
+ "array([1.2636038, 1.126463 , 1.3123759, 1.2140924, 1.1805094],\n",
664
+ " dtype=float32)"
665
+ ]
666
+ },
667
+ "execution_count": 11,
668
+ "metadata": {},
669
+ "output_type": "execute_result"
670
+ }
671
+ ],
672
  "source": [
673
  "results = ablang(all_seqs, mode='confidence')\n",
674
  "np.exp(-results)"
 
686
  },
687
  {
688
  "cell_type": "code",
689
+ "execution_count": 12,
690
  "id": "2d5b725c-4eac-4a4b-9331-357c3ac140f7",
691
  "metadata": {},
692
+ "outputs": [
693
+ {
694
+ "data": {
695
+ "text/plain": [
696
+ "array(['<EVQLLESGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCARDVPGHGAAFMDVWGTGTTVTVSS>|<DIQLTQSPLSLPVTLGQPASISCRSSQSLEASDTNIYLSWFQQRPGQSPRRLIYKISNRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK>',\n",
697
+ " '<EVQLLESGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCARDVPGHGAAFMDVWGTGTT>|<PVTLGQPASISCRSSQSLEASDTNIYLSWFQQRPGQSPRRLIYKISNRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK>',\n",
698
+ " '<EVQLVQSGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCARDPPGHGAAFMDVWGTGTTVTVSS>|<DIQLTQSPLSLPVTLGQPASISCRSSQSLEASDTNIYLSWFQQRPGQSPRRLIYKISNRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK>'],\n",
699
+ " dtype='<U238')"
700
+ ]
701
+ },
702
+ "execution_count": 12,
703
+ "metadata": {},
704
+ "output_type": "execute_result"
705
+ }
706
+ ],
707
  "source": [
708
  "restored = ablang(only_both_chains_seqs, mode='restore')\n",
709
  "restored"
 
711
  },
712
  {
713
  "cell_type": "code",
714
+ "execution_count": 13,
715
  "id": "0e9615f7-c490-4947-96f4-7617266c686e",
716
  "metadata": {},
717
+ "outputs": [
718
+ {
719
+ "data": {
720
+ "text/plain": [
721
+ "array(['<EVQLLESGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCARDVPGHGAAFMDVWGTGTTVTVSS>|<DIQLTQSPLSLPVTLGQPASISCRSSQSLEASDTNIYLSWFQQRPGQSPRRLIYKISNRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK>',\n",
722
+ " '<EVQLLESGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCARDVPGHGAAFMDVWGTGTTVTVSS>|<DVVMTQSPLSLPVTLGQPASISCRSSQSLEASDTNIYLSWFQQRPGQSPRRLIYKISNRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK>',\n",
723
+ " '<QVQLVQSGGEVKKPGASVKVSCRASGYTFRNYGLTWVRQAPGQGLEWMGWISAYNGNTNYAQKFQGRVTLTTDTSTSTAYMELRSLRSDDTAVYFCARDPPGHGAAFMDVWGTGTTVTVSS>|<DIQLTQSPLSLPVTLGQPASISCRSSQSLEASDTNIYLSWFQQRPGQSPRRLIYKISNRDSGVPDRFSGSGSGTHFTLRISRVEADDVAVYYCMQGTHWPPAFGQGTKVDIK>'],\n",
724
+ " dtype='<U238')"
725
+ ]
726
+ },
727
+ "execution_count": 13,
728
+ "metadata": {},
729
+ "output_type": "execute_result"
730
+ }
731
+ ],
732
  "source": [
733
  "restored = ablang(only_both_chains_seqs, mode='restore', align = True)\n",
734
  "restored"