Can't load model in AWS Lambda
The code itself runs perfectly fine on my laptop as well as after creating a docker image.try:
    from bs4 import BeautifulSoup
    import requests
    from urllib.request import urlopen
    import base64
    import re
    from transformers import BartForConditionalGeneration, BartTokenizer, BartConfig
    import json
except Exception as e:
    print("Error imports : {} ".format(e))

def lambda_handler(event=None, context=None):
    headers = {'User-Agent': 'Mozilla/5.0'}

    url = 'https://news.google.com/news/rss'
    client = urlopen(url)
    xml_page = client.read()
    client.close()
    soup = BeautifulSoup(xml_page, 'xml')

    contents = soup.find_all("item")

    encoded_links = []
    headlines = []
    dates = []

    for news in contents:
        if "youtube.com" in str(news.source):
            continue
        encoded_links.append(news.link.text)
        headlines.append(news.title.text)
        dates.append(news.pubDate.text)

    encoded_links = encoded_links[:15]
    headlines = headlines[:15]
    dates = dates[:15]

    decoded_links = []

    for link in encoded_links:
        coded = link[44:-5]
        while True:
            try:
                url = base64.b64decode(coded)
                break
            except:
                coded += "a"
        url = str(base64.b64decode(coded))

        strip1 = re.search("(?P<url>https?://[^\s]+)", url).group("url")
        strip2 = stripped = strip1.split('$', 1)[0]
        strip3 = stripped = strip2.split('\\', 1)[0]
        decoded_links.append(strip3)

    summarized_texts = []

    tokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn', cache_dir="/tmp/")
    model=BartForConditionalGeneration.from_pretrained('facebook/bart-large-cnn', cache_dir="/tmp/")

    for link in decoded_links:
        try:
            new_page = requests.get(link, headers=headers)
        except:
            continue
        new_soup  = BeautifulSoup(new_page.text, 'lxml')
        
        text = ""
        paragraphs = new_soup.find_all("p")
        for p in paragraphs:
            text += p.text

        inputs = tokenizer.batch_encode_plus([text],return_tensors='pt', truncation=True, max_length=1024)
        summary_ids = model.generate(inputs['input_ids'], early_stopping=True)

        bart_summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)

        summarized_texts.append(bart_summary)
        print(bart_summary)

    returned = [{'headline': title, 'date': date, 'summary': summarized} for title, date, summarized in zip(headlines, dates, summarized_texts)]

    json_summaries = json.dumps(returned)

    return json_summariesBut when uploaded to AWS Lambda (using aws ecr), I run into an error.{
  "errorMessage": "Can't load the model for 'facebook/bart-large-cnn'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'facebook/bart-large-cnn' is the correct path to a directory containing a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack.",
  "errorType": "OSError",
  "requestId": "938ad716-f2c2-4d18-920b-f170aa685b4c",
  "stackTrace": [
    "  File \"/var/task/app.py\", line 59, in lambda_handler
    model=BartForConditionalGeneration.from_pretrained('facebook/bart-large-cnn',cache_dir=\"/tmp/\")",
    "  File \"/var/lang/lib/python3.9/site-packages/transformers/modeling_utils.py\", line 2023, in from_pretrained\n    raise EnvironmentError("
  ]
}I don’t know what this error means, as the code runs fine on my machine and docker, meaning it’s not an issue with the code.