together-common-errors

Together AI common errors for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together common errors".

1,868 stars

Best use case

together-common-errors is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Together AI common errors for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together common errors".

Teams using together-common-errors should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/together-common-errors/SKILL.md --create-dirs "https://raw.githubusercontent.com/jeremylongshore/claude-code-plugins-plus-skills/main/plugins/saas-packs/together-pack/skills/together-common-errors/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/together-common-errors/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How together-common-errors Compares

Feature / Agenttogether-common-errorsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Together AI common errors for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together common errors".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Together AI Common Errors

## Overview

Together AI provides OpenAI-compatible inference, fine-tuning, and batch processing across 100+ open-source models (Llama, Mixtral, Qwen, FLUX). Common errors include model-not-available failures when requesting deprecated or gated models, token limit violations that differ per model architecture, and fine-tune job failures from dataset formatting issues. The API is compatible with any OpenAI client library at `base_url = 'https://api.together.xyz/v1'`. Model IDs use the full namespace format (e.g., `meta-llama/Meta-Llama-3.1-8B-Instruct`) and must match exactly. This reference covers inference, fine-tuning, and deployment errors.

## Error Reference

| Code | Message | Cause | Fix |
|------|---------|-------|-----|
| `401` | `Unauthorized` | Invalid or missing `TOGETHER_API_KEY` | Verify key at api.together.xyz > Settings |
| `400` | `Model not found` | Wrong model ID or model deprecated | Use `client.models.list()` to get valid model IDs |
| `400` | `Token limit exceeded` | Input + max_tokens exceeds model context | Reduce input length or lower `max_tokens` parameter |
| `400` | `Invalid fine-tune dataset` | JSONL format errors or missing required fields | Each line must be valid JSON with `messages` array |
| `402` | `Insufficient credits` | Account balance depleted | Add credits at api.together.xyz > Billing |
| `404` | `Fine-tune job not found` | Invalid job ID or job expired | List active jobs with `client.fine_tuning.list()` |
| `429` | `Rate limit exceeded` | Too many concurrent requests | Implement backoff; use batch API for 50% cost reduction |
| `500` | `Model overloaded` | High demand on specific model | Retry with backoff; try alternative model of same family |

## Error Handler

```typescript
interface TogetherError {
  code: number;
  message: string;
  category: "auth" | "rate_limit" | "validation" | "billing";
}

function classifyTogetherError(status: number, body: string): TogetherError {
  if (status === 401) {
    return { code: 401, message: body, category: "auth" };
  }
  if (status === 402) {
    return { code: 402, message: body, category: "billing" };
  }
  if (status === 429) {
    return { code: 429, message: "Rate limit exceeded", category: "rate_limit" };
  }
  return { code: status, message: body, category: "validation" };
}
```

## Debugging Guide

### Authentication Errors
Together uses Bearer token authentication. Pass `TOGETHER_API_KEY` via `Authorization: Bearer` header or set it in the client constructor. Keys do not expire but can be revoked. If using the OpenAI client library, set `base_url='https://api.together.xyz/v1'` and pass the Together key as `api_key`.

### Rate Limit Errors
Rate limits vary by plan tier and are enforced per-key. Free tier allows 5 requests/second; paid tiers scale higher. Use the batch inference API (`/v1/batch`) for non-real-time workloads at 50% cost reduction. Check `X-RateLimit-Remaining` header to monitor quota.

### Validation Errors
Model IDs must match exactly (e.g., `meta-llama/Meta-Llama-3.1-8B-Instruct`). Use `client.models.list()` to enumerate available models. Token limits vary per model -- Llama 3.1 supports 128K context while older models may support only 4K. Fine-tune datasets must be JSONL with each line containing a `messages` array in chat format. Empty `messages` arrays or missing `role` fields cause silent validation failures. Validate each JSONL line independently before uploading.

## Error Handling

| Scenario | Pattern | Recovery |
|----------|---------|----------|
| Model deprecated | 400 with "not found" | Check model list; migrate to successor model |
| Token limit exceeded | 400 on long prompts | Truncate input or use model with larger context window |
| Fine-tune dataset rejected | JSONL validation errors | Validate each line independently; fix and re-upload |
| Credits depleted mid-batch | 402 after N successful calls | Add credits, resume from last successful request |
| Model overloaded at peak | 500 on popular models | Fall back to alternative model in same family |

## Quick Diagnostic

```bash
# Verify API connectivity and list available models
curl -s -o /dev/null -w "%{http_code}" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  https://api.together.xyz/v1/models
```

## Resources

- [Together AI Documentation](https://docs.together.ai/)
- [API Reference](https://docs.together.ai/reference/chat-completions-1)
- [Supported Models](https://docs.together.ai/docs/inference-models)

## Next Steps

See `together-debug-bundle`.

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