Instructions to use benchflow/benchflow-qwen35-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use benchflow/benchflow-qwen35-9b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B") model = PeftModel.from_pretrained(base_model, "benchflow/benchflow-qwen35-9b") - Notebooks
- Google Colab
- Kaggle
| library_name: peft | |
| base_model: Qwen/Qwen3.5-9B | |
| pipeline_tag: text-generation | |
| datasets: | |
| - benchflow/env0-experiment-trajectories | |
| tags: | |
| - base_model:adapter:Qwen/Qwen3.5-9B | |
| - lora | |
| - peft | |
| - sft | |
| - env-0 | |
| - openhands | |
| - daytona | |
| - qwen397b | |
| # BenchFlow Qwen3.5-9B Env-0 Qwen397B-Data Custom SFT LoRA Adapter | |
| This repository contains the current BenchFlow env-0 SFT adapter for `Qwen/Qwen3.5-9B`. It is a PEFT LoRA adapter only; load it with the base `Qwen/Qwen3.5-9B` checkpoint. | |
| ## Current Version | |
| | Field | Value | | |
| | --- | --- | | |
| | Adapter repo | `benchflow/benchflow-qwen35-9b` | | |
| | Published model PR | [HF PR #4](https://huggingface.co/benchflow/benchflow-qwen35-9b/discussions/4) | | |
| | Adapter commit promoted from PR | `92380a83764ec2d8b2103a3895e24e49a508d1d9` | | |
| | Training run id | `qwen35-397b-data-qwen35-9b-custom-sft-20260630T042600Z` | | |
| | Base checkpoint | `Qwen/Qwen3.5-9B` | | |
| | Adapter type | LoRA / PEFT | | |
| | Trainer | Custom PyTorch + PEFT LoRA trainer, `experiments/env-0-posttrain-mvp/train_lora_sft.py` | | |
| | Source data | Qwen3.5-397B teacher trajectories collected with BenchFlow, OpenHands, and Daytona | | |
| | Training rows | `298` all-training-ready rows | | |
| | Hardware | 1x H100 80GB | | |
| This run used the historical custom trainer. Prime-RL was not used as the SFT trainer; the source data path includes `prime-rl` only because the trajectories were also validated and exported in Prime-SFT-compatible format. | |
| ## Training Recipe | |
| | Field | Value | | |
| | --- | --- | | |
| | Precision | BF16 | | |
| | Quantization | None | | |
| | Context length | `8192` | | |
| | Max trainer steps | `300` micro-batch steps | | |
| | Micro batch size | `1` | | |
| | Gradient accumulation | `8` | | |
| | Approx optimizer updates | `37` | | |
| | Learning rate | `1e-4` | | |
| | Scheduler | None | | |
| | Max grad norm | `1.0` | | |
| | LoRA rank | `32` | | |
| | LoRA alpha | `64` | | |
| | LoRA dropout | `0.05` | | |
| | LoRA targets | `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` | | |
| | Checkpoints | `100`, `200`, `300`, `best_adapter`, `final_adapter` | | |
| | Final eval loss | `0.1476329118013382` | | |
| ## Evaluation Results | |
| | Evaluation | Runtime | Strict pass | | |
| | --- | --- | ---: | | |
| | Mobile300 | SGLang | `135 / 300` | | |
| | Mobile300 | Fireworks | `134 / 300` | | |
| | standard60, 3 trials | Fireworks | `25 / 180` | | |
| ## Artifact Links | |
| | Artifact | Link | | |
| | --- | --- | | |
| | Source teacher trajectories | [HF dataset folder](https://huggingface.co/datasets/benchflow/env0-experiment-trajectories/tree/main/experiments/qwen35-397b-env0-mini-prime-rl-trajectories/20260629-qwen35-397b-openrouter-openhands-daytona/canonical/train-mini-300-combined-qwen35-397b-20260629T2336Z) | | |
| | Training artifacts | [HF dataset folder](https://huggingface.co/datasets/benchflow/env0-experiment-trajectories/tree/main/experiments/qwen35-397b-env0-mini-custom-sft/training/qwen35-397b-data-qwen35-9b-custom-sft-20260630T042600Z) | | |
| | Fireworks Mobile300 eval | [HF dataset folder](https://huggingface.co/datasets/benchflow/env0-experiment-trajectories/tree/main/experiments/qwen35-397b-env0-mini-custom-sft/eval/fireworks-qwen397b-custom-sft-mobile300-20260630T084904Z) | | |
| | Fireworks standard60 eval | [HF dataset folder](https://huggingface.co/datasets/benchflow/env0-experiment-trajectories/tree/main/experiments/qwen35-397b-env0-mini-custom-sft/eval/fireworks-qwen397b-custom-sft-standard60-3trials-20260630T172230Z) | | |
| | Reproduction report | [GitHub report](https://github.com/benchflow-ai/env-0-experiment/blob/main/experiments/qwen35-397b-env0-mini-custom-sft/reports/2026-06-30-qwen397b-custom-sft-reproduction-parameters.md) | | |
| ## Loading | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| from peft import PeftModel | |
| base_id = "Qwen/Qwen3.5-9B" | |
| adapter_id = "benchflow/benchflow-qwen35-9b" | |
| tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True) | |
| base_model = AutoModelForCausalLM.from_pretrained( | |
| base_id, | |
| torch_dtype="auto", | |
| device_map="auto", | |
| trust_remote_code=True, | |
| ) | |
| model = PeftModel.from_pretrained(base_model, adapter_id) | |
| ``` | |
| ## Intended Use And Limitations | |
| This adapter is an env-0 research artifact for controlled BenchFlow/OpenHands/Daytona evaluation. It is not a general-purpose safety-tested assistant model and should not be treated as production-ready for autonomous operation. | |