XXHStudyHard/EnvScaler-SFT-Scenario
EnvScaler-SFT-Scenario Dataset Description Usage Note: The init_config field is stored as a JSON string. You need to use json.loads() to convert it to a dictionary when using the dataset. This dataset contains 4,684 supervised fine-tuning (SFT) scenarios generated by the EnvScaler framework. Each scenario consists of an environment configuration and a task description for training LLM agents in tool-interactive environments. EnvScaler is an automated, scalable… See the full description on the dataset page: https://huggingface.co/datasets/XXHStudyHard/EnvScaler-SFT-Scenario.
| Author / organization | XXHStudyHard |
|---|---|
| License (as declared) | mit |
| Downloads | 132 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 9 January 2026 |
| Last updated at source | 15 January 2026 |
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- 16 Oct 2026 Description: EnvScaler-SFT-Scenario Dataset Description Usage Note: The init_config field is stored as a JSON string. You need to use json.loads() to convert it to a dictionary when using the dataset. This dataset contains 4,684 supervised fine-tuning ( → EnvScaler-SFT-Scenario Dataset Description Usage Note: The init_config field is stored as a JSON string. You need to use json.loads() to convert it to a dictionary when using the dataset. This dataset contains 4,684 supervised fine-tuning (
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