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a/notebooks/HuggingFace-Inference.ipynb b/notebooks/HuggingFace-Inference.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b974278ad901491b7b4cdc2445c25f4f13a8a0d1 --- /dev/null +++ b/notebooks/HuggingFace-Inference.ipynb @@ -0,0 +1,832 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 5, + "id": "9837afb7", + "metadata": {}, + "outputs": [], + "source": [ + "def generate_prompt(instruction: str, input_ctxt: str = None) -> str:\n", + " if input_ctxt:\n", + " return f\"\"\"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n", + "\n", + "### Instruction:\n", + "{instruction}\n", + "\n", + "### Input:\n", + "{input_ctxt}\n", + "\n", + "### Response:\"\"\"\n", + " else:\n", + " return f\"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n", + "\n", + "### Instruction:\n", + "{instruction}\n", + "\n", + "### Response:\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "1cb5103c", + "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" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bff8fb0a005e4635a07ecf6fe0fdba88", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Loading checkpoint shards: 0%| | 0/33 [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/transformers/modeling_utils.py:45 │\n", + "│ 9 in load_state_dict │\n", + "│ │\n", + "│ 456 │ │ │ ) │\n", + "│ 457 │ │ return safe_load_file(checkpoint_file) │\n", + "│ 458 │ try: │\n", + "│ ❱ 459 │ │ return torch.load(checkpoint_file, map_location=\"cpu\") │\n", + "│ 460 │ except Exception as e: │\n", + "│ 461 │ │ try: │\n", + "│ 462 │ │ │ with open(checkpoint_file) as f: │\n", + "│ │\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/torch/serialization.py:791 in │\n", + "│ load │\n", + "│ │\n", + "│ 788 │ if 'encoding' not in pickle_load_args.keys(): │\n", + "│ 789 │ │ pickle_load_args['encoding'] = 'utf-8' │\n", + "│ 790 │ │\n", + "│ ❱ 791 │ with _open_file_like(f, 'rb') as opened_file: │\n", + "│ 792 │ │ if _is_zipfile(opened_file): │\n", + "│ 793 │ │ │ # The zipfile reader is going to advance the current file position. │\n", + "│ 794 │ │ │ # If we want to actually tail call to torch.jit.load, we need to │\n", + "│ │\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/torch/serialization.py:271 in │\n", + "│ _open_file_like │\n", + "│ │\n", + "│ 268 │\n", + "│ 269 def _open_file_like(name_or_buffer, mode): │\n", + "│ 270 │ if _is_path(name_or_buffer): │\n", + "│ ❱ 271 │ │ return _open_file(name_or_buffer, mode) │\n", + "│ 272 │ else: │\n", + "│ 273 │ │ if 'w' in mode: │\n", + "│ 274 │ │ │ return _open_buffer_writer(name_or_buffer) │\n", + "│ │\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/torch/serialization.py:252 in │\n", + "│ __init__ │\n", + "│ │\n", + "│ 249 │\n", + "│ 250 class _open_file(_opener): │\n", + "│ 251 │ def __init__(self, name, mode): │\n", + "│ ❱ 252 │ │ super().__init__(open(name, mode)) │\n", + "│ 253 │ │\n", + "│ 254 │ def __exit__(self, *args): │\n", + "│ 255 │ │ self.file_like.close() │\n", + "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n", + "FileNotFoundError: [Errno 2] No such file or directory: \n", + "'../decapoda-research/llama-7b-hf/pytorch_model-00001-of-00033.bin'\n", + "\n", + "During handling of the above exception, another exception occurred:\n", + "\n", + "╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮\n", + "│ in <module>:16 │\n", + "│ │\n", + "│ 13 │\n", + "│ 14 tokenizer = LlamaTokenizer.from_pretrained(MODEL_NAME) │\n", + "│ 15 │\n", + "│ ❱ 16 model = LlamaForCausalLM.from_pretrained( │\n", + "│ 17 │ BASE_MODEL, │\n", + "│ 18 │ load_in_8bit=True, │\n", + "│ 19 │ torch_dtype=torch.float16, │\n", + "│ │\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/transformers/modeling_utils.py:28 │\n", + "│ 70 in from_pretrained │\n", + "│ │\n", + "│ 2867 │ │ │ │ mismatched_keys, │\n", + "│ 2868 │ │ │ │ offload_index, │\n", + "│ 2869 │ │ │ │ error_msgs, │\n", + "│ ❱ 2870 │ │ │ ) = cls._load_pretrained_model( │\n", + "│ 2871 │ │ │ │ model, │\n", + "│ 2872 │ │ │ │ state_dict, │\n", + "│ 2873 │ │ │ │ loaded_state_dict_keys, # XXX: rename? │\n", + "│ │\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/transformers/modeling_utils.py:32 │\n", + "│ 02 in _load_pretrained_model │\n", + "│ │\n", + "│ 3199 │ │ │ │ # Skip the load for shards that only contain disk-offloaded weights when │\n", + "│ 3200 │ │ │ │ if shard_file in disk_only_shard_files: │\n", + "│ 3201 │ │ │ │ │ continue │\n", + "│ ❱ 3202 │ │ │ │ state_dict = load_state_dict(shard_file) │\n", + "│ 3203 │ │ │ │ │\n", + "│ 3204 │ │ │ │ # Mistmatched keys contains tuples key/shape1/shape2 of weights in the c │\n", + "│ 3205 │ │ │ │ # matching the weights in the model. │\n", + "│ │\n", + "│ /opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/transformers/modeling_utils.py:46 │\n", + "│ 2 in load_state_dict │\n", + "│ │\n", + "│ 459 │ │ return torch.load(checkpoint_file, map_location=\"cpu\") │\n", + "│ 460 │ except Exception as e: │\n", + "│ 461 │ │ try: │\n", + "│ ❱ 462 │ │ │ with open(checkpoint_file) as f: │\n", + "│ 463 │ │ │ │ if f.read(7) == \"version\": │\n", + "│ 464 │ │ │ │ │ raise OSError( │\n", + "│ 465 │ │ │ │ │ │ \"You seem to have cloned a repository without having git-lfs ins │\n", + "╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\n", + "FileNotFoundError: [Errno 2] No such file or directory: \n", + "'../decapoda-research/llama-7b-hf/pytorch_model-00001-of-00033.bin'\n", + "\n" + ], + "text/plain": [ + "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/transformers/\u001b[0m\u001b[1;33mmodeling_utils.py\u001b[0m:\u001b[94m45\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[94m9\u001b[0m in \u001b[92mload_state_dict\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 456 \u001b[0m\u001b[2m│ │ │ \u001b[0m) \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 457 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m safe_load_file(checkpoint_file) \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 458 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mtry\u001b[0m: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 459 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m torch.load(checkpoint_file, map_location=\u001b[33m\"\u001b[0m\u001b[33mcpu\u001b[0m\u001b[33m\"\u001b[0m) \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 460 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mexcept\u001b[0m \u001b[96mException\u001b[0m \u001b[94mas\u001b[0m e: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 461 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mtry\u001b[0m: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 462 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94mwith\u001b[0m \u001b[96mopen\u001b[0m(checkpoint_file) \u001b[94mas\u001b[0m f: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/torch/\u001b[0m\u001b[1;33mserialization.py\u001b[0m:\u001b[94m791\u001b[0m in \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[92mload\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 788 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mif\u001b[0m \u001b[33m'\u001b[0m\u001b[33mencoding\u001b[0m\u001b[33m'\u001b[0m \u001b[95mnot\u001b[0m \u001b[95min\u001b[0m pickle_load_args.keys(): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 789 \u001b[0m\u001b[2m│ │ \u001b[0mpickle_load_args[\u001b[33m'\u001b[0m\u001b[33mencoding\u001b[0m\u001b[33m'\u001b[0m] = \u001b[33m'\u001b[0m\u001b[33mutf-8\u001b[0m\u001b[33m'\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 790 \u001b[0m\u001b[2m│ \u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 791 \u001b[2m│ \u001b[0m\u001b[94mwith\u001b[0m _open_file_like(f, \u001b[33m'\u001b[0m\u001b[33mrb\u001b[0m\u001b[33m'\u001b[0m) \u001b[94mas\u001b[0m opened_file: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 792 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m _is_zipfile(opened_file): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 793 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[2m# The zipfile reader is going to advance the current file position.\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 794 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[2m# If we want to actually tail call to torch.jit.load, we need to\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/torch/\u001b[0m\u001b[1;33mserialization.py\u001b[0m:\u001b[94m271\u001b[0m in \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[92m_open_file_like\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 268 \u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 269 \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_open_file_like\u001b[0m(name_or_buffer, mode): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 270 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mif\u001b[0m _is_path(name_or_buffer): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 271 \u001b[2m│ │ \u001b[0m\u001b[94mreturn\u001b[0m _open_file(name_or_buffer, mode) \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 272 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94melse\u001b[0m: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 273 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[94mif\u001b[0m \u001b[33m'\u001b[0m\u001b[33mw\u001b[0m\u001b[33m'\u001b[0m \u001b[95min\u001b[0m mode: \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 274 \u001b[0m\u001b[2m│ │ │ \u001b[0m\u001b[94mreturn\u001b[0m _open_buffer_writer(name_or_buffer) \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2;33m/opt/conda/envs/media-reco-env-3-8/lib/python3.8/site-packages/torch/\u001b[0m\u001b[1;33mserialization.py\u001b[0m:\u001b[94m252\u001b[0m in \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[92m__init__\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 249 \u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 250 \u001b[0m\u001b[94mclass\u001b[0m \u001b[4;92m_open_file\u001b[0m(_opener): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 251 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__init__\u001b[0m(\u001b[96mself\u001b[0m, name, mode): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 252 \u001b[2m│ │ \u001b[0m\u001b[96msuper\u001b[0m().\u001b[92m__init__\u001b[0m(\u001b[96mopen\u001b[0m(name, mode)) \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 253 \u001b[0m\u001b[2m│ \u001b[0m \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 254 \u001b[0m\u001b[2m│ \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m__exit__\u001b[0m(\u001b[96mself\u001b[0m, *args): \u001b[31m│\u001b[0m\n", + "\u001b[31m│\u001b[0m \u001b[2m 255 \u001b[0m\u001b[2m│ │ \u001b[0m\u001b[96mself\u001b[0m.file_like.close() \u001b[31m│\u001b[0m\n", + "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n", + "\u001b[1;91mFileNotFoundError: \u001b[0m\u001b[1m[\u001b[0mErrno \u001b[1;36m2\u001b[0m\u001b[1m]\u001b[0m No such file or directory: \n", + "\u001b[32m'../decapoda-research/llama-7b-hf/pytorch_model-00001-of-00033.bin'\u001b[0m\n", + "\n", + "\u001b[3mDuring handling of the above exception, another exception occurred:\u001b[0m\n", + "\n", + "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n", + "\u001b[31m│\u001b[0m in \u001b[92m