XXHStudyHard/EnvScaler-SFT-Traj-9K
EnvScaler-SFT-Traj-9K Dataset Description Usage Note: The tools, messages, and user_messages fields are stored as JSON strings. You need to use json.loads() to convert them to lists/dictionaries when using the dataset. This dataset contains 9,022 supervised fine-tuning (SFT) trajectories generated by the EnvScaler framework. Each trajectory records the complete interaction history between an LLM agent and a tool-interactive environment, including the… See the full description on the dataset page: https://huggingface.co/datasets/XXHStudyHard/EnvScaler-SFT-Traj-9K.
| Author / organization | XXHStudyHard |
|---|---|
| License (as declared) | mit |
| Downloads | 267 (as reported by Hugging Face) |
| Likes | 6 |
| Created | 8 January 2026 |
| Last updated at source | 7 March 2026 |
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267 now (+4 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
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- 16 Oct 2026 Description: EnvScaler-SFT-Traj-9K Dataset Description Usage Note: The tools, messages, and user_messages fields are stored as JSON strings. You need to use json.loads() to convert them to lists/dictionaries when using the dataset. This dataset contains → EnvScaler-SFT-Traj-9K Dataset Description Usage Note: The tools, messages, and user_messages fields are stored as JSON strings. You need to use json.loads() to convert them to lists/dictionaries when using the dataset. This dataset contains
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