Skip to content

Commit 3ba85a7

Browse files
authored
docs: update README.md and add data card for OneVision Encoder training data (#39)
1 parent 79724a2 commit 3ba85a7

2 files changed

Lines changed: 8 additions & 5 deletions

File tree

README.md

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -14,9 +14,9 @@
1414

1515
📝 **[Homepage](https://www.lmms-lab.com/onevision-encoder/index.html)**
1616
🤗 **[Models](https://huggingface.co/lmms-lab-encoder/onevision-encoder-large)** |
17-
🤗 **[Datasets](coming)** |
1817
📄 **[Tech Report (coming)]()** |
19-
📋 **[Model Card](docs/model_card.md)**
18+
📋 **[Model Card](docs/model_card.md)** |
19+
📊 **[Data Card](docs/data_card.md)**
2020

2121
</div>
2222

@@ -283,7 +283,7 @@ cd eval_encoder
283283
Then run the following command:
284284

285285
```bash
286-
bash eval_encoder/shells_eval_ap/eval_ov_encoder_large_16frames.sh
286+
bash shells_eval_ap/eval_ov_encoder_large_16frames.sh
287287
```
288288

289289
**Sampling-Specific Parameters:**
@@ -320,8 +320,8 @@ torchrun --nproc_per_node=8 --master_port=29512 attentive_probe_codec.py \
320320

321321
**Codec-Specific Parameters:**
322322
- `K_keep`: Number of patches to keep.
323-
- `cache_dir`: Directory for cached codec patches. This is where the codec-selected patches will be stored/loaded.
324323
- `mv_compensate`: Motion vector compensation method (e.g., `median`).
324+
- `cache_dir` (optional): Directory for cached codec patches. Use this to specify where codec-selected patches are stored/loaded when you want to persist or reuse them.
325325

326326
#### Shared Parameters
327327

docs/datacard.md renamed to docs/data_card.md

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,8 +1,11 @@
11
# Data Card: OneVision Encoder Training Data
22

3+
> **📦 Data Availability Notice:** The training data requires approximately **200TB** of storage. We are currently looking for suitable storage solutions. If you need access to the data immediately, please contact [anxiangsir@outlook.com](mailto:anxiangsir@outlook.com).
4+
5+
36
## Overview
47

5-
This document describes the datasets used for training OneVision Encoder. The training data consists of both image and video datasets, totaling approximately 754 million samples.
8+
This document describes the datasets used for training OneVision Encoder. The training data consists of both image and video datasets.
69

710
## Dataset Summary
811

0 commit comments

Comments
 (0)