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Merge branch 'main' into chore/bump_transformers_v5

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This commit is contained in:
Steven Palma
2026-03-04 17:41:33 +01:00
committed by GitHub
parent fb3ddd6a48 0d1be72dc8
commit 62bbd6165c
9 changed files with 210 additions and 106 deletions
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docs/source/earthrover_mini_plus.mdx
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@@ -170,13 +170,13 @@ Once you can drive the robot well, you can start recording data to train AI mode
We use Hugging Face to store your data online. First, log in with your token from [Hugging Face settings](https://huggingface.co/settings/tokens):
```bash
huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
hf auth login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
```
Store your Hugging Face username:
```bash
HF_USER=$(huggingface-cli whoami | head -n 1)
HF_USER=$(hf auth whoami | awk -F': *' 'NR==1 {print $2}')
echo $HF_USER
```
docs/source/envhub.mdx
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@@ -155,10 +155,10 @@ Upload your repository to Hugging Face:
pip install huggingface_hub
# Login to Hugging Face
huggingface-cli login
hf auth login
# Create a new repository
huggingface-cli repo create my-custom-env --type space --org my-org
hf repo create my-org/my-custom-env
# Initialize git and push
git init
docs/source/il_robots.mdx
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@@ -159,7 +159,7 @@ We use the Hugging Face hub features for uploading your dataset. If you haven't
Add your token to the CLI by running this command:
```bash
huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
hf auth login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
```
Then store your Hugging Face repository name in a variable:
@@ -327,7 +327,7 @@ You can look for other LeRobot datasets on the hub by searching for `LeRobot` [t
You can also push your local dataset to the Hub manually, running:
```bash
huggingface-cli upload ${HF_USER}/record-test ~/.cache/huggingface/lerobot/{repo-id} --repo-type dataset
hf upload ${HF_USER}/record-test ~/.cache/huggingface/lerobot/{repo-id} --repo-type dataset
```
#### Record function
@@ -491,7 +491,7 @@ If your local computer doesn't have a powerful GPU you could utilize Google Cola
Once training is done, upload the latest checkpoint with:
```bash
huggingface-cli upload ${HF_USER}/act_so101_test \
hf upload ${HF_USER}/act_so101_test \
outputs/train/act_so101_test/checkpoints/last/pretrained_model
```
@@ -499,7 +499,7 @@ You can also upload intermediate checkpoints with:
```bash
CKPT=010000
huggingface-cli upload ${HF_USER}/act_so101_test${CKPT} \
hf upload ${HF_USER}/act_so101_test${CKPT} \
outputs/train/act_so101_test/checkpoints/${CKPT}/pretrained_model
```
docs/source/lekiwi.mdx
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@@ -279,13 +279,13 @@ We use the Hugging Face hub features for uploading your dataset. If you haven't
Add your token to the CLI by running this command:
```bash
huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
hf auth login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
```
Then store your Hugging Face repository name in a variable:
```bash
HF_USER=$(huggingface-cli whoami | head -n 1)
HF_USER=$(hf auth whoami | awk -F': *' 'NR==1 {print $2}')
echo $HF_USER
```