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
Add README.md
Browse files
README.md
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---
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license: apache-2.0
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tags:
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- robotics
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- vla
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- lingbot-vla
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- pot14
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library_name: transformers
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---
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# lingbot_pot14
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LingBot-VLA 在 **pot14 自采右臂数据**上微调到 `global_step_1024` 的部署权重。
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- 基座: [robbyant/lingbot-vla-4b](https://huggingface.co/robbyant/lingbot-vla-4b)
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- 任务: 杯子等(训练文本形如 `完成任务:杯子`)
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- 动作: 7 维单活动臂(6 关节 + 1 effector)
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- 相机: top / left / right(由拼接画面裁剪)
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## 仓库内容
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| 路径 | 说明 |
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|------|------|
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| `model-*.safetensors` + `config.json` 等 | HF 格式权重(`hf_ckpt`) |
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| `configs/pot14_right_arm.json` | 归一化统计量 |
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| `configs/robot_pot14.yaml` | 机器人特征映射 |
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| `configs/vla_pot14.yaml` | 训练配置参考 |
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## 下载
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```bash
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export HF_ENDPOINT=https://hf-mirror.com # 国内可选
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huggingface-cli download coisini9293/lingbot_pot14 \
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--local-dir models/finetuned/lingbot_pot14
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```
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推理还需要 Qwen 处理器:
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```bash
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huggingface-cli download Qwen/Qwen2.5-VL-3B-Instruct \
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--local-dir models/pretrained/Qwen2.5-VL-3B-Instruct
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```
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完整训练 / 云端推理 / 本地串口说明见项目文档
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`docs/pot14_full_guide.md`。
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