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

# 身份验证

> 配置 API 令牌和身份验证

# 身份验证

为 Hugging Face Hub 和 W\&B 配置身份验证。

## Hugging Face 令牌

### 环境变量

```bash theme={null}
export HF_TOKEN="hf_xxxxxxxxxxxxxxxxxxxxx"
```

### 在 Python 中

```python theme={null}
from autotrain.trainers.clm.params import LLMTrainingParams

params = LLMTrainingParams(
    model="google/gemma-3-270m",
    data_path="./data.jsonl",
    project_name="my-model",
    token="hf_xxxxxxxxxxxxxxxxxxxxx",  # HF token
)
```

### 获取令牌

1. 访问 [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
2. 点击 "New token"
3. 选择 "Write" 访问权限以推送到 hub
4. 复制令牌

## W\&B 令牌

### 环境变量

```bash theme={null}
export WANDB_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
```

### 在 Python 中

```python theme={null}
params = LLMTrainingParams(
    model="google/gemma-3-270m",
    data_path="./data.jsonl",
    project_name="my-model",
    log="wandb",
    wandb_token="xxxxxxxxxxxxxxxxxxxxxxxx",
)
```

### 获取令牌

1. 访问 [wandb.ai/authorize](https://wandb.ai/authorize)
2. 复制您的 API 密钥

## 推送到 Hub

将模型推送到 Hugging Face Hub：

```python theme={null}
params = LLMTrainingParams(
    model="google/gemma-3-270m",
    data_path="./data.jsonl",
    project_name="my-model",
    push_to_hub=True,
    username="your-hf-username",
    token="hf_xxxxxxxxxxxxxxxxxxxxx",
)
```

## 私有模型

使用您的令牌访问私有模型：

```python theme={null}
# Set environment variable
import os
os.environ["HF_TOKEN"] = "hf_xxxxxxxxxxxxxxxxxxxxx"

# Or pass directly
params = LLMTrainingParams(
    model="your-org/private-model",
    data_path="./data.jsonl",
    project_name="my-model",
    token="hf_xxxxxxxxxxxxxxxxxxxxx",
)
```

## 私有数据集

访问私有数据集：

```python theme={null}
params = LLMTrainingParams(
    model="google/gemma-3-270m",
    data_path="your-org/private-dataset",  # HF dataset ID
    project_name="my-model",
    token="hf_xxxxxxxxxxxxxxxxxxxxx",
)
```

## 安全令牌处理

### 使用 .env 文件

```bash theme={null}
# .env
HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxx
WANDB_API_KEY=xxxxxxxxxxxxxxxxxxxxxxxx
```

```python theme={null}
from dotenv import load_dotenv
import os

load_dotenv()

params = LLMTrainingParams(
    model="google/gemma-3-270m",
    data_path="./data.jsonl",
    project_name="my-model",
    token=os.getenv("HF_TOKEN"),
)
```

### 切勿提交令牌

添加到 `.gitignore`：

```
.env
*.token
```

## 下一步

<CardGroup cols={2}>
  <Card title="Python SDK" href="/api/python-sdk">
    完整 API 参考
  </Card>

  <Card title="LLM Endpoints" href="/api/llm-endpoints">
    LLM 训练 API
  </Card>
</CardGroup>