Fix: GGUF File Loading Failure From Local Folder

Nov 12, 2025 by Alex Johnson 49 views

Troubleshooting GGUF File Loading Errors from Local Folders

Are you encountering issues while trying to load a GGUF file from your local directory? This comprehensive guide will walk you through the common pitfalls and provide step-by-step solutions to get your model up and running. We'll dissect a real-world bug report, analyze the error messages, and equip you with the knowledge to diagnose and resolve similar problems. So, let's dive in and ensure your GGUF files load smoothly.

Understanding the GGUF File Format

Before we delve into troubleshooting, let's briefly discuss the GGUF (GGML Unified Format) file format. GGUF is a file format designed to store models, particularly large language models (LLMs), in a way that is efficient and easy to use. It's the successor to the GGML format and offers several advantages, including better support for metadata and improved compatibility across different hardware and software platforms.

When working with models in GGUF format, it's crucial to understand how your application or library expects the files to be organized and accessed. Misconfigurations in file paths or access permissions can often lead to loading errors. Keeping this in mind, let’s proceed to debug the reported issue.

Decoding the Bug: Unable to Load GGUF File

Let's examine a specific bug report to understand the common issues developers face when loading GGUF files. The user, EricLBuehler, reported an issue with the mistral.rs library, where loading a GGUF model from a local folder consistently failed. The provided code snippet and error logs offer valuable clues to diagnose the problem.

Analyzing the Code Snippet

Here's the snippet of Rust code that attempts to load the GGUF model:

let model_dir = PathBuf::from("../models/abc");
println!("Loading model from {}", model_dir.display().to_string());

let model = GgufModelBuilder::new(
    model_dir.display().to_string(),
    vec!["Qwen3-4B-Instruct-2507-Q4_K_M.gguf"],
)
.with_logging()
.with_tokenizer_json(model_dir.join("tokenizer.json").display().to_string())
.with_chat_template(model_dir.join("chat_template.json").display().to_string())
.with_paged_attn(|| {
    PagedAttentionMetaBuilder::default()
        .with_gpu_memory(MemoryGpuConfig::ContextSize(12384))
        .with_block_size(32)
        .build()
})?
.build()
.await?;

The code constructs a GgufModelBuilder to load the model. It specifies the model directory, the GGUF file name (Qwen3-4B-Instruct-2507-Q4_K_M.gguf), the tokenizer JSON file, and the chat template JSON file. The PagedAttentionMetaBuilder configures memory management.

Interpreting the Error Logs

The error logs provide critical insights into the failure:

Loading model from ../models/adc
2025-11-12T18:45:05.891488Z  INFO hf_hub: Using token file found "/Users/vish/.cache/huggingface/token"
2025-11-12T18:45:06.262160Z  WARN mistralrs_core::pipeline::gguf: Could not get directory listing from API: RequestError(Status(404, Response[status: 404, status_text: Not Found, url: https://huggingface.co/api/models/adc/revision/main]))
2025-11-12T18:45:06.262591Z  INFO mistralrs_core::pipeline::gguf: Using chat template file at `../models/adc/chat_template.json`
2025-11-12T18:45:06.262901Z  INFO hf_hub: Using token file found "/Users/vish/.cache/huggingface/token"

thread 'main' (1979138) panicked at /Users/vish/.cargo/git/checkouts/mistral.rs-d7a5d833e16ad691/ddc63ce/mistralrs-core/src/pipeline/paths.rs:342:28:
Could not get file "Qwen3-4B-Instruct-2507-Q4_K_M.gguf" from API: RequestError(Status(404, Response[status: 404, status_text: Not Found, url: https://huggingface.co/models/adc/resolve/main/Qwen3-4B-Instruct-2507-Q4_K_M.gguf]))

Key observations from the logs include:

The application attempts to load the model from the ../models/adc directory.
It tries to fetch a directory listing from the Hugging Face API but receives a 404 error. This suggests that the application is, by default, trying to fetch the model from the Hugging Face Model Hub.
The application then attempts to load the chat template file locally, which succeeds.
The final panic indicates that the application could not retrieve the GGUF file (Qwen3-4B-Instruct-2507-Q4_K_M.gguf) from the Hugging Face API, again resulting in a 404 error.

Diagnosing the Root Cause

The primary issue here is that the application is attempting to fetch the GGUF file from the Hugging Face Model Hub, even though the intention is to load it from a local folder. This is evident from the 404 errors when trying to access https://huggingface.co/api/models/adc/revision/main and https://huggingface.co/models/adc/resolve/main/Qwen3-4B-Instruct-2507-Q4_K_M.gguf.

The mistral.rs library, by default, might be configured to look for models in the Hugging Face Model Hub unless explicitly told otherwise. The code seems to provide a local path (../models/adc), but the library's internal logic might still be prioritizing the online repository.

Step-by-Step Solutions to Resolve the Issue

To successfully load the GGUF file from the local folder, we need to ensure that the mistral.rs library is correctly configured to prioritize the local file path. Here’s a step-by-step approach to resolving this issue:

1. Verify the Local File Path

First, double-check that the local file path specified in the code is correct and that the GGUF file actually exists at that location. Incorrect file paths are a common source of loading errors. In the provided code, the path is ../models/adc. Ensure that this path is relative to the execution directory of your Rust application.

Use the following steps to verify the file path:

Print the current working directory in your application to understand the context for relative paths.
Manually check if the GGUF file (Qwen3-4B-Instruct-2507-Q4_K_M.gguf) exists in the specified directory.
Confirm that there are no typos in the file name or directory path.

2. Configure the Library to Use Local Files

Most libraries that support loading models from both local paths and remote repositories have configuration options to specify the source. For mistral.rs, there might be a specific way to instruct the GgufModelBuilder to load files locally.

Check the Library Documentation: Refer to the mistral.rs documentation to find the correct way to specify that the model should be loaded from a local path. Look for options or methods related to local file loading or disabling remote repository access.
Configuration Flags: There might be configuration flags or settings that you can set to prioritize local files. For example, some libraries have an option to set a local_only flag or a similar setting.

3. Disable Hugging Face Hub Access (If Necessary)

If the library continues to attempt to access the Hugging Face Model Hub, even after specifying the local path, you might need to explicitly disable the Hub access. This can often be done through environment variables or configuration settings.

Environment Variables: Some libraries use environment variables to control their behavior. Check if mistral.rs has an environment variable that disables or prioritizes local file loading. For example, a variable like MISTRAL_LOCAL_ONLY or HF_HUB_OFFLINE might exist.
Configuration Objects: The library might provide a configuration object or struct where you can set options to disable remote access. Look for options like disable_hub or offline_mode.

4. Provide Absolute Paths

As a more robust solution, consider using absolute paths instead of relative paths. Absolute paths eliminate ambiguity and ensure that the library correctly locates the files, regardless of the execution directory.

Construct Absolute Paths: Use Rust's std::env::current_dir() to get the current working directory and then construct the absolute path to your model files.

use std::env;
use std::path::PathBuf;

fn get_absolute_path(relative_path: &str) -> PathBuf {
    let mut current_dir = env::current_dir().expect("Failed to get current directory");
    current_dir.push(relative_path);
    current_dir
}

let model_dir = get_absolute_path("../models/adc");
println!("Loading model from {}", model_dir.display().to_string());

5. Handle File Permissions

Ensure that your application has the necessary permissions to read the GGUF file and related files (tokenizer JSON, chat template JSON). Permission issues can prevent the library from accessing the files, resulting in loading errors.

Check File Permissions: Verify that the user account running the application has read permissions for the model directory and the GGUF file.
Adjust Permissions: If necessary, adjust the file permissions using your operating system's tools (e.g., chmod on Linux/macOS).

6. Review Library Updates and Known Issues

Check the mistral.rs library's issue tracker or release notes for any known bugs or updates related to local file loading. There might be a recently discovered issue or a fix that addresses your problem.

GitHub Issues: Browse the library's GitHub repository for open or closed issues that match your problem description.
Release Notes: Review the release notes for the latest versions of the library to see if any relevant fixes or improvements have been included.

Applying the Solutions to the Bug Report

Based on the error logs and the troubleshooting steps, we can now suggest specific solutions to EricLBuehler for their bug report:

Verify the File Path: Double-check that the ../models/adc path is correct relative to where the Rust application is executed. Ensure that the Qwen3-4B-Instruct-2507-Q4_K_M.gguf file exists in this directory.
Configure Local File Loading: Consult the mistral.rs documentation to find the correct way to specify that the GGUF file should be loaded from the local file system. Look for any specific methods or options in the GgufModelBuilder that control this behavior.
Disable Hugging Face Hub Access (If Necessary): If the library continues to attempt to access the Hugging Face Model Hub, look for a way to disable this behavior. Check for environment variables or configuration options that might control Hub access.

Use Absolute Paths: Modify the code to use absolute paths for the model directory and the GGUF file. This can help eliminate any ambiguity in file paths.

use std::env;
use std::path::PathBuf;

fn get_absolute_path(relative_path: &str) -> PathBuf {
    let mut current_dir = env::current_dir().expect("Failed to get current directory");
    current_dir.push(relative_path);
    current_dir
}

let model_dir = get_absolute_path("../models/adc");
println!("Loading model from {}", model_dir.display().to_string());

let model = GgufModelBuilder::new(
    model_dir.display().to_string(),
    vec!["Qwen3-4B-Instruct-2507-Q4_K_M.gguf"],
)
.with_logging()
.with_tokenizer_json(get_absolute_path("../models/adc/tokenizer.json").display().to_string())
.with_chat_template(get_absolute_path("../models/adc/chat_template.json").display().to_string())
.with_paged_attn(|| {
    PagedAttentionMetaBuilder::default()
        .with_gpu_memory(MemoryGpuConfig::ContextSize(12384))
        .with_block_size(32)
        .build()
})?
.build()
.await?;

By following these steps, EricLBuehler should be able to resolve the issue and successfully load the GGUF file from the local folder.

General Best Practices for GGUF File Management

To prevent GGUF file loading issues, consider these best practices:

Consistent File Paths: Use consistent and well-defined file paths throughout your application. Avoid hardcoding paths; instead, use configuration settings or environment variables.
Proper Error Handling: Implement robust error handling to catch file loading errors and provide informative error messages to users.
File Integrity Checks: Consider adding file integrity checks (e.g., checksum validation) to ensure that the GGUF file has not been corrupted.
Regularly Update Libraries: Keep your libraries (like mistral.rs) up to date to benefit from bug fixes and performance improvements.
Documentation and Comments: Document your code and configuration settings clearly, especially file paths and loading procedures.

Conclusion

Loading GGUF files from local folders can sometimes present challenges, but with a systematic approach to troubleshooting, you can quickly identify and resolve the issues. By understanding the error messages, verifying file paths, configuring libraries correctly, and following best practices, you can ensure a smooth and efficient model loading process.

Remember, the key to successful debugging is a combination of careful analysis, methodical testing, and a thorough understanding of the tools and libraries you are using. Happy coding!

For additional information on file handling and Rust programming, you may find helpful resources on the official Rust documentation.