> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fireworks.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Training troubleshooting

> Solutions for common training deployment and access issues.

## Access issues

**Q: Why am I getting "Model not found" errors when trying to access my trained model?**

If you’re unable to access your trained model, try these troubleshooting steps:

**First steps**:

* Attempt to access the model through both the **playground** and the **API**.
* Check if the error occurs for **all users** on the account.
* Ensure your **API key** is valid.

**Common causes**:

* User email previously associated with a **deleted account**
* **API key permissions** issues
* **Access conflicts** due to multiple accounts

**Debug process**:

1. Verify the API key’s validity using:
   ```bash theme={null}
   curl -v -H "Authorization: Bearer $FIREWORKS_API_KEY" https://api.fireworks.ai/verifyApiKey
   ```
2. Check if the issue persists across different **API keys**.
3. Identify which specific **users/emails** are affected.

**Getting help**:

* Contact support with:
  * Your **account ID**
  * **API key verification** results
  * A list of **affected users/emails**
  * Results from both **playground** and **API** tests

*Note*: If you have multiple accounts, ensure that access permissions are checked across all of them.

***

## Troubleshooting firectl deployment

**Q: Why am I getting "invalid id" errors when using firectl commands like create deployment or list deployments?**

This error typically occurs when your **account ID** is not properly configured.

### Common symptoms

* Error message: `invalid id: id must be at least 1 character long`
* Affects multiple commands, including:
  * `firectl deployment create`
  * `firectl deployment list`

To resolve:

### Steps to resolve

1. Run `firectl whoami` to check which **account id** is being used.
2. Ensure the correct **account ID** is being used. If not, run `firectl signin` to sign-in to the right account.

***

## LoRA deployment issues

**Q: Why can’t I deploy my trained Llama 3.1 LoRA adapter?**

If you encounter the following error:

```bash theme={null}
Invalid LoRA weight model.layers.0.self_attn.q_proj.lora_A.weight shape: torch.Size([16, 4096]), expected (16, 8192)
```

This issue is due to the `fireworks.json` file being set to **Llama 3.1 70b instruct** by default.

**Workaround**:

1. Download the **model weights**.
2. Modify the base model to be `accounts/fireworks/models/llama-v3p1-8b-instruct`.
3. Follow the instructions in the [documentation](https://fireworks.ai/fine-tuning/model-upload) to upload and deploy the model.

***

## Additional information

If you experience any issues during these processes, you can:

* Contact support through Discord at [discord.gg/fireworks-ai](https://discord.gg/fireworks-ai)
* Reach out to your account representative (Enterprise customers)
* Email [inquiries@fireworks.ai](mailto:inquiries@fireworks.ai)