Getting "Connection errored" bug when using Hugging Face Transformers
Author: eben-vranken
Pull request: no

**Description:**

I am getting the "`Connection errored`" bug when I try to use Hugging Face Transformers to load a model from the Hugging Face Hub. I have tried updating Hugging Face Transformers to the latest version, but the problem persists.


**Expected behavior:**

The model should be loaded successfully.


**Actual behavior:**

I get the following error message:
`ValueError: Connection errored`

**`Code`:**
```python
from transformers import AutoTokenizer, AutoModelForCausalLM, logging
import torch
import gradio as gr
from pathlib import Path

access_token = "private"
DATA_PATH = Path("./")
MODEL_NAME = "stabilityai/stablecode-instruct-alpha-3b"

# Define the model and tokenizer names for saving
model_save_name = "stablecode-instruct-alpha-3b"
tokenizer_save_name = "stablecode-instruct-alpha-3b_tokenizer"

# Set up logging
logging.set_verbosity_error()  # Set the logging level to error to avoid unnecessary messages

def load_or_train_model():
    # Load the model from Hugging Face Hub as usual
    model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, trust_remote_code=True, torch_dtype="auto", token=access_token)
    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=access_token)

    # Save the loaded model and tokenizer to the persistent storage
    model.save_pretrained(model_save_name)
    tokenizer.save_pretrained(tokenizer_save_name)

    return model, tokenizer

def get_or_load_model():
    try:
        # Try to load the model and tokenizer from the persistent storage
        model = AutoModelForCausalLM.from_pretrained(model_save_name)
        tokenizer = AutoTokenizer.from_pretrained(tokenizer_save_name)
    except:
        # If the model or tokenizer doesn't exist in persistent storage, load and save them
        model, tokenizer = load_or_train_model()

    return model, tokenizer

# Load or get the model and tokenizer
model, tokenizer = get_or_load_model()

def text_generation(input_text):
    if tokenizer is None or model is None:
        return "Error: Model not loaded"
    
    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
    outputs = model.generate(input_ids, num_beams=4, do_sample=True, max_new_tokens=48, temperature=0.2)
    generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
    return generated_text

# Vue Property Decorator -> Options API
def propertyDecoratorRemoval(input_code):
    prompt = f"Perform a seamless migration from 'vue-property-decorator' code to the native Vue options API for the provided code snippet. Ensure that the refactoring maintains the functionality of the original code while leveraging the benefits of the Vue options API. Following is the code: {input_code}"
    agent_answer = text_generation(prompt)
    return agent_answer

propertyDecoratorRemovalTab = gr.Interface(
    fn=propertyDecoratorRemoval,
    article="This tab will take the inputted code (which utilizes the vue-property-decorator package) and migrates it to the native Options API in Vue.",
    inputs=gr.Textbox(lines=30, placeholder="vue-property-decorator code here..."),
    outputs=gr.Textbox(lines=30, placeholder="Options API code will be outputted here...")
)

# Vue Property Decorator -> Options API
def vueVersionMigration(input_code):
    return "Migration"

vueVersionMigrationTab = gr.Interface(
    fn=vueVersionMigration,
    description="❗ Please ensure that your code does not have any breaking changes when migrated to Vue 3.",
    article="This tab takes the inputted Vue 2 code and migrates it to Vue 3.",
    inputs=gr.Textbox(lines=30, placeholder="To migrate Vue 2 here..."),
    outputs=gr.Textbox(lines=30, placeholder="Migrated Vue 3 code will be outputted here...")
)

gr.TabbedInterface([propertyDecoratorRemovalTab, vueVersionMigrationTab], ["Vue Property Decorator removal", "Vue Version Migration"]).launch(allowed_paths=[str(DATA_PATH)])
```

Comments:
#https://github.com/huggingface/huggingface_hub/issues/1632

Hey! Thanks for opening a PR. 
I can't really debug this for you as is, since you did not provide a full traceback of the error, and you need to also share the output of `transformers-cli envs` this way I can know which packages you have installed. 

I ran the script you shared, and got no erros:
<img width="1588" alt="image" src="https://github.com/huggingface/transformers/assets/48595927/89094549-5223-4795-b57d-da60b9f4fd66">