Instructions to use coisini9293/lingbot_pot14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coisini9293/lingbot_pot14 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("coisini9293/lingbot_pot14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from coisini9293/lingbot_pot14: direct link, hf CLI and curl.
- Browser
- Download file 1.26 kB
-
https://huggingface.co/coisini9293/lingbot_pot14/resolve/main/README.md
- Command line
-
hf download hf://coisini9293/lingbot_pot14/README.md
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curl -L -o README.md https://huggingface.co/coisini9293/lingbot_pot14/resolve/main/README.md
1.26 kB
| license: apache-2.0 | |
| tags: | |
| - robotics | |
| - vla | |
| - lingbot-vla | |
| - pot14 | |
| library_name: transformers | |
| # lingbot_pot14 | |
| LingBot-VLA 在 **pot14 自采右臂数据**上微调到 `global_step_1024` 的部署权重。 | |
| - 基座: [robbyant/lingbot-vla-4b](https://huggingface.co/robbyant/lingbot-vla-4b) | |
| - 任务: 杯子等(训练文本形如 `完成任务:杯子`) | |
| - 动作: 7 维单活动臂(6 关节 + 1 effector) | |
| - 相机: top / left / right(由拼接画面裁剪) | |
| ## 仓库内容 | |
| | 路径 | 说明 | | |
| |------|------| | |
| | `model-*.safetensors` + `config.json` 等 | HF 格式权重(`hf_ckpt`) | | |
| | `configs/pot14_right_arm.json` | 归一化统计量 | | |
| | `configs/robot_pot14.yaml` | 机器人特征映射 | | |
| | `configs/vla_pot14.yaml` | 训练配置参考 | | |
| ## 下载 | |
| ```bash | |
| export HF_ENDPOINT=https://hf-mirror.com # 国内可选 | |
| huggingface-cli download coisini9293/lingbot_pot14 \ | |
| --local-dir models/finetuned/lingbot_pot14 | |
| ``` | |
| 推理还需要 Qwen 处理器: | |
| ```bash | |
| huggingface-cli download Qwen/Qwen2.5-VL-3B-Instruct \ | |
| --local-dir models/pretrained/Qwen2.5-VL-3B-Instruct | |
| ``` | |
| 完整训练 / 云端推理 / 本地串口说明见项目文档 | |
| `docs/pot14_full_guide.md`。 | |