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chore(docs): updating deprecated huggingface-cli to hf (#3071)
* chore(docs): updating deprecated huggingface-cli to hf * small typo in my-org
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@@ -170,13 +170,13 @@ Once you can drive the robot well, you can start recording data to train AI mode
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We use Hugging Face to store your data online. First, log in with your token from [Hugging Face settings](https://huggingface.co/settings/tokens):
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We use Hugging Face to store your data online. First, log in with your token from [Hugging Face settings](https://huggingface.co/settings/tokens):
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```bash
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```bash
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huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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hf auth login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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```
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```
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Store your Hugging Face username:
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Store your Hugging Face username:
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```bash
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```bash
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HF_USER=$(huggingface-cli whoami | head -n 1)
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HF_USER=$(hf auth whoami | awk -F': *' 'NR==1 {print $2}')
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echo $HF_USER
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echo $HF_USER
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```
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```
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@@ -155,10 +155,10 @@ Upload your repository to Hugging Face:
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pip install huggingface_hub
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pip install huggingface_hub
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# Login to Hugging Face
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# Login to Hugging Face
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huggingface-cli login
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hf auth login
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# Create a new repository
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# Create a new repository
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huggingface-cli repo create my-custom-env --type space --org my-org
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hf repo create my-org/my-custom-env
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# Initialize git and push
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# Initialize git and push
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git init
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git init
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@@ -159,7 +159,7 @@ We use the Hugging Face hub features for uploading your dataset. If you haven't
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Add your token to the CLI by running this command:
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Add your token to the CLI by running this command:
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```bash
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```bash
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huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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hf auth login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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```
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```
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Then store your Hugging Face repository name in a variable:
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Then store your Hugging Face repository name in a variable:
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@@ -327,7 +327,7 @@ You can look for other LeRobot datasets on the hub by searching for `LeRobot` [t
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You can also push your local dataset to the Hub manually, running:
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You can also push your local dataset to the Hub manually, running:
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```bash
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```bash
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huggingface-cli upload ${HF_USER}/record-test ~/.cache/huggingface/lerobot/{repo-id} --repo-type dataset
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hf upload ${HF_USER}/record-test ~/.cache/huggingface/lerobot/{repo-id} --repo-type dataset
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```
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```
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#### Record function
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#### Record function
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@@ -491,7 +491,7 @@ If your local computer doesn't have a powerful GPU you could utilize Google Cola
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Once training is done, upload the latest checkpoint with:
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Once training is done, upload the latest checkpoint with:
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```bash
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```bash
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huggingface-cli upload ${HF_USER}/act_so101_test \
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hf upload ${HF_USER}/act_so101_test \
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outputs/train/act_so101_test/checkpoints/last/pretrained_model
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outputs/train/act_so101_test/checkpoints/last/pretrained_model
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```
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```
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@@ -499,7 +499,7 @@ You can also upload intermediate checkpoints with:
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```bash
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```bash
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CKPT=010000
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CKPT=010000
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huggingface-cli upload ${HF_USER}/act_so101_test${CKPT} \
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hf upload ${HF_USER}/act_so101_test${CKPT} \
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outputs/train/act_so101_test/checkpoints/${CKPT}/pretrained_model
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outputs/train/act_so101_test/checkpoints/${CKPT}/pretrained_model
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```
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```
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@@ -279,13 +279,13 @@ We use the Hugging Face hub features for uploading your dataset. If you haven't
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Add your token to the CLI by running this command:
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Add your token to the CLI by running this command:
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```bash
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```bash
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huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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hf auth login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential
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```
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```
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Then store your Hugging Face repository name in a variable:
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Then store your Hugging Face repository name in a variable:
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```bash
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```bash
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HF_USER=$(huggingface-cli whoami | head -n 1)
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HF_USER=$(hf auth whoami | awk -F': *' 'NR==1 {print $2}')
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echo $HF_USER
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echo $HF_USER
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```
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```
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