README.md

---
base_model:
- Qwen/Qwen3-8B
datasets:
- open-thoughts/OpenThoughts-Agent-SFT-ColdStartForRL-10K
library_name: transformers
license: apache-2.0
model-index:
- name: OpenThinkerAgent-8B-ColdStartSFTForRL
  results: []
pipeline_tag: text-generation
tags:
- agents
- terminal
- code
- software-engineering
- sft
- cold-start
---
<p align="center">
    <img src="https://huggingface.co/datasets/open-thoughts/OpenThoughts1-Agent-SFT/resolve/main/ota-logo.png" width="50%">
</p>

<p align="center">
<a href="https://www.openthoughts.ai/blog/agent" style="margin-right: 24px;">Project</a> |
<a href="https://github.com/open-thoughts/OpenThoughts-Agent" style="margin-right: 24px; margin-left: 24px;">Code</a> |
<a href="https://huggingface.co/collections/open-thoughts/openthinker-agent" style="margin-left: 24px;">Collection</a>
</p>


# OpenThinkerAgent-8B-ColdStartSFTForRL

**OpenThoughts-Agent** is an open-source effort to curate the best datasets for training agents. Our release includes [datasets](https://huggingface.co/collections/open-thoughts/openthinker-agent), [models](https://huggingface.co/collections/open-thoughts/openthinker-agent) and our [research codebase](https://github.com/open-thoughts/OpenThoughts-Agent).

[OpenThinkerAgent-8B-ColdStartSFTForRL](https://huggingface.co/open-thoughts/OpenThinkerAgent-8B-ColdStartSFTForRL) is the **cold-start, pre-RL base** of the OpenThoughts-Agent 8B SFT→RL recipe. It is post-trained from [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) with full-parameter SFT on the cold-start [OpenThoughts-Agent-SFT-ColdStartForRL-10K](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-SFT-ColdStartForRL-10K) dataset. Its purpose is to give the model the agentic interaction format and tool-use behaviour needed to make subsequent reinforcement learning stable; it is then RL-trained to produce [OpenThinkerAgent-8B-RL](https://huggingface.co/open-thoughts/OpenThinkerAgent-8B-RL).

> **Architecture note.** Although the upstream artifact carries a `GLM-4.7` label (which refers to the *teacher* that generated the SFT trajectories, not the student), this model is a **Qwen3-8B**. Its `config.json` reports `model_type: qwen3`, `architectures: ["Qwen3ForCausalLM"]`, 36 layers, hidden size 4096, 32 attention heads / 8 KV heads, and a 40,960-token context — i.e. standard Qwen3-8B.

- **Homepage:** https://www.openthoughts.ai/blog/agent
- **Repository:** https://github.com/open-thoughts/OpenThoughts-Agent

# Model details

- **Base model:** [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B)
- **Architecture:** Qwen3 (`Qwen3ForCausalLM`), 36 layers, hidden size 4096, 32 attention heads, 8 KV heads, RoPE θ = 1e6
- **Context length:** 40,960 tokens (max position embeddings)
- **Vocabulary:** 151,936 tokens
- **Precision:** bf16
- **Role in pipeline:** cold-start SFT checkpoint (pre-RL base)

# Position in the SFT → RL recipe

1. [OpenThoughts-Agent-SFT-ColdStartForRL-10K](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-SFT-ColdStartForRL-10K) — cold-start SFT trajectories.
2. **[OpenThinkerAgent-8B-ColdStartSFTForRL](https://huggingface.co/open-thoughts/OpenThinkerAgent-8B-ColdStartSFTForRL)** — this model (Qwen3-8B after cold-start SFT, the pre-RL base).
3. [OpenThoughts-Agent-RL-5K](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-RL-5K) — on-policy RL tasks.
4. [OpenThinkerAgent-8B-RL](https://huggingface.co/open-thoughts/OpenThinkerAgent-8B-RL) — the final RL'd checkpoint (step 45).

# Training data

Trained on [OpenThoughts-Agent-SFT-ColdStartForRL-10K](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-SFT-ColdStartForRL-10K) (**9,437** (task, trajectory) pairs): SWE-Smith sandboxed coding tasks with tests, solved by a teacher model in the **terminus-2** harness inside Daytona sandboxes, oracle-verified (120s verifier timeout).

# Training procedure

Full-parameter SFT (LLaMA-Factory). Hyperparameters as recorded by the trainer:

- learning_rate: 4e-05
- lr_scheduler_type: cosine, warmup_ratio 0.1
- train_batch_size: 1 per device × 8 devices × gradient_accumulation_steps 2 → total_train_batch_size 16
- optimizer: AdamW (fused), betas (0.9, 0.98), eps 1e-08
- num_epochs: 7
- seed: 42
- precision: bf16
- final train loss: ≈ 0.303 (4,130 global steps)

### Framework versions
- Transformers 4.57.6
- PyTorch 2.9.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.2

# Intended uses & limitations

This checkpoint is intended as the **starting point for agentic RL**, not as a final deployable agent. It has learned the agentic format and tool-use conventions of the terminus-2 harness from a relatively small cold-start set; its standalone agentic performance is expected to be below the RL-trained successor [OpenThinkerAgent-8B-RL](https://huggingface.co/open-thoughts/OpenThinkerAgent-8B-RL). As with the base Qwen3-8B, outputs may be incorrect or unsafe and should not be executed without review. No standalone agentic-benchmark numbers are published for this cold-start checkpoint.

# Links
- 🌐 [OpenThoughts-Agent project page](https://www.openthoughts.ai/blog/agent)
- 💻 [OpenThoughts-Agent GitHub repository](https://github.com/open-thoughts/OpenThoughts-Agent)
- 📚 [OpenThinker-Agent collection](https://huggingface.co/collections/open-thoughts/openthinker-agent)
- 🧠 [Training dataset: OpenThoughts-Agent-SFT-ColdStartForRL-10K](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-SFT-ColdStartForRL-10K)
- 🧠 [RL tasks: OpenThoughts-Agent-RL-5K](https://huggingface.co/datasets/open-thoughts/OpenThoughts-Agent-RL-5K)
- 🤖 [Final RL model: OpenThinkerAgent-8B-RL](https://huggingface.co/open-thoughts/OpenThinkerAgent-8B-RL)

# Citation
```
@misc{openthoughts-agent,
  author = {Team, OpenThoughts-Agent},
  title = {{OpenThoughts-Agent: Data Recipes for Agentic Models}},
  howpublished = {https://www.openthoughts.ai/blog/agent},
  year = {2026}
}
```