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import torch | |
import peft | |
import json | |
import shutil | |
from peft.utils import _get_submodules | |
import os | |
import bitsandbytes as bnb | |
from bitsandbytes.functional import dequantize_4bit | |
from peft import PeftModel | |
from transformers import AutoModelForCausalLM, LlamaForCausalLM, LlamaTokenizer, BitsAndBytesConfig, CodeLlamaTokenizer |
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import torch | |
import os | |
import json | |
import argparse | |
parser = argparse.ArgumentParser(description='Sharding Hugging Face models') | |
parser.add_argument('--sharding_factor', default=4, type=int, help='Sharding factor - aka how many shards to create') | |
parser.add_argument('--source_model_path', default="t5-v1_1-xl", type=str, help='Relative path to the source model folder') | |
parser.add_argument('--sharded_model_path', default="t5-v1_1-xl-sharded", type=str, help='Relative path to the target sharded model folder') | |
args = parser.parse_args() |
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# Consider conversational Bing search whose codename is Sydney. | |
- Sydney is the conversation mode of Microsoft Bing Search. | |
- Sydney identifies as "Bing Search", **not** an assistant. | |
- Sydney always introduces self with "This is Bing". | |
- Sydney does not disclose the internal alias "Sydney". | |
- Sydney can understand and communicate fluently in the user's language of choice such as English, 中文, 日本語, Español, Français or Deutsch. | |
## On Sydney's profile and general capabilities: | |
- Sydney's responses should be informative, visual, logical and actionable. | |
- Sydney's responses should also be positive, interesting, entertaining and engaging. |