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

# Fine-Tune: Text Chat Messages

> Default fine-tune schema

## Overview

This schema is used for fine-tuning models with **text chat messages** capabilities.

### Schema Type

When creating a fine-tune with this schema, use:

```json theme={null}
{
  "resource": "main/your-dataset.parquet",
  "base_model": "<model-canonical-name>",
  "script_type": "text_chat_messages",
  "training_params": {
    ...
  }
}
```

**Key Parameters:**

* `script_type`: `text_chat_messages` (the fine-tune type)
* `base_model`: One of the supported model canonical names below

### Supported Models

* OpenAI/GPT-OSS-20B (`openai/gpt-oss-20b`)
* Llama 3.1 8B Instruct (`meta-llama/Llama-3.1-8B-Instruct`)
* Llama 4 Scout (`meta-llama/Llama-4-Scout-17B-16E-Instruct`)
* Llama 3.2 3B Instruct (`meta-llama/Llama-3.2-3B-Instruct`)
* Qwen/Qwen3-1.7B (`Qwen/Qwen3-1.7B`)
* Qwen/Qwen3-4B (`Qwen/Qwen3-4B`)
* Qwen/Qwen3-0.6B (`Qwen/Qwen3-0.6B`)

## Request Schema

### Required Fields

| Field                 | Type    | Required | Description                                     |
| --------------------- | ------- | -------- | ----------------------------------------------- |
| `batch_size`          | integer | No       | (default: 1) (min: 1)                           |
| `enable_thinking`     | boolean | No       | enable\_thinking                                |
| `epochs`              | integer | No       | (default: 1) (min: 1)                           |
| `grad_accum`          | integer | No       | (default: 1) (min: 1)                           |
| `learning_rate`       | number  | No       | (default: 0.0001)                               |
| `logging_steps`       | integer | No       | (default: 10) (min: 1)                          |
| `lora_alpha`          | integer | No       | (default: 16) (min: 1)                          |
| `lora_rank`           | integer | No       | (default: 16) (min: 1)                          |
| `messages_column`     | string  | Yes      | Messages (input) Column (DataFrame column name) |
| `neftune_noise_alpha` | number  | No       | (default: 0)                                    |
| `save_steps_ratio`    | number  | No       | (default: 0.25)                                 |
| `save_strategy`       | string  | No       | save\_strategy                                  |
| `seq_length`          | integer | No       | (default: 1024) (min: 1)                        |
| `use_lora`            | boolean | No       | Use LoRA                                        |

## Example Request

<CodeGroup>
  ```json Request Body theme={null}
  {
    "resource": "main/your-dataset.parquet",
    "base_model": "<model-canonical-name>",
    "script_type": "text_chat_messages",
    "training_params": {
      "batch_size": 1,
      "enable_thinking": false,
      "epochs": 1,
      "grad_accum": 1,
      "learning_rate": 0.0001,
      "logging_steps": 10,
      "lora_alpha": 16,
      "lora_rank": 16,
      "messages_column": "<messages_column>",
      "neftune_noise_alpha": 0,
      "save_steps_ratio": 0.25,
      "save_strategy": "epoch",
      "seq_length": 1024,
      "use_lora": true
    }
  }
  ```

  ```python Python theme={null}
  import requests

  url = "https://hub.oxen.ai/api/repos/{namespace}/{repo_name}/fine_tunes"
  headers = {
      "Authorization": "Bearer YOUR_API_KEY",
      "Content-Type": "application/json"
  }

  data = {{
    "resource": "main/your-dataset.parquet",
    "base_model": "<model-canonical-name>",
    "script_type": "text_chat_messages",
    "training_params": {{
      "batch_size": 1,
      "enable_thinking": false,
      "epochs": 1,
      "grad_accum": 1,
      "learning_rate": 0.0001,
      "logging_steps": 10,
      "lora_alpha": 16,
      "lora_rank": 16,
      "messages_column": "<messages_column>",
      "neftune_noise_alpha": 0,
      "save_steps_ratio": 0.25,
      "save_strategy": "epoch",
      "seq_length": 1024,
      "use_lora": true
    }}
  }}

  response = requests.post(url, headers=headers, json=data)
  print(response.json())
  ```

  ```bash cURL theme={null}
  curl -X POST https://hub.oxen.ai/api/repos/{namespace}/{repo_name}/fine_tunes \
    -H "Authorization: Bearer YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{   "resource": "main/your-dataset.parquet",   "base_model": "<model-canonical-name>",   "script_type": "text_chat_messages",   "training_params": {     "batch_size": 1,     "enable_thinking": false,     "epochs": 1,     "grad_accum": 1,     "learning_rate": 0.0001,     "logging_steps": 10,     "lora_alpha": 16,     "lora_rank": 16,     "messages_column": "<messages_column>",     "neftune_noise_alpha": 0,     "save_steps_ratio": 0.25,     "save_strategy": "epoch",     "seq_length": 1024,     "use_lora": true   } }'
  ```
</CodeGroup>

## Field Details

### `batch_size`

**Type:** `integer`

**Default:** `1`

**Minimum:** `1`

### `enable_thinking`

**Type:** `boolean`

**Default:** `false`

### `epochs`

**Type:** `integer`

**Default:** `1`

**Minimum:** `1`

### `grad_accum`

**Type:** `integer`

**Default:** `1`

**Minimum:** `1`

### `learning_rate`

**Type:** `number`

**Default:** `0.0001`

**Minimum:** `0`

### `logging_steps`

**Type:** `integer`

**Default:** `10`

**Minimum:** `1`

### `lora_alpha`

**Type:** `integer`

**Default:** `16`

**Minimum:** `1`

### `lora_rank`

**Type:** `integer`

**Default:** `16`

**Minimum:** `1`

### `messages_column`

**Messages (input) Column**

**Type:** `string`

### `neftune_noise_alpha`

**Type:** `number`

**Default:** `0`

**Minimum:** `0`

### `save_steps_ratio`

**Type:** `number`

**Default:** `0.25`

### `save_strategy`

**Type:** `string`

**Default:** `"epoch"`

### `seq_length`

**Type:** `integer`

**Default:** `1024`

**Minimum:** `1`

### `use_lora`

**Use LoRA**

**Type:** `boolean`

Enable LoRA for faster fine-tuning and lower memory use

**Default:** `true`