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
File size: 1,259 Bytes
980e44a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | ---
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`。
|