hf downloader doc (#416)

* hf downloader doc

Signed-off-by: Andrews Arokiam <[email protected]>

* review comment changes

Signed-off-by: Andrews Arokiam <[email protected]>

* Update hf.md

---------

Signed-off-by: Andrews Arokiam <[email protected]>
Co-authored-by: Dan Sun <[email protected]>

docs/modelserving/storage/huggingface/hf.md

@@ -0,0 +1,121 @@
+# Deploy InferenceService with model from Hugging Face(HF) Hub
+
+You can specify the `storageUri` field on `InferenceService` YAML with the following format to deploy the models from Hugging Face Hub.
+
+```
+hf://${REPO}/${MODEL}:${HASH}(optional)
+```
+
+e.g. ```hf://facebook/opt-125m```
+
+## Public Hugging Face Models
+
+If no credential is provided, anonymous client will be used to download the model from HF repo.
+
+## Private Hugging Face Models
+
+KServe supports authenticating with `HF_TOKEN` for downloading the model and create a Kubernetes secret to store the HF token.
+
+=== "yaml"
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: storage-config
+type: Opaque
+data:
+  HF_TOKEN: aGZfVk5Vd1JVAUdCa0l4WmZMTHVrc2VHeW9VVm9udU5pBHUVT==
+```
+
+
+## Deploy InferenceService with Models from HF Hub
+
+### Option 1: Use Service Account with Secret Ref
+Create a Kubernetes `ServiceAccount` with the HF token secret name reference and specify the `ServiceAccountName` in the `InferenceService` Spec.
+
+=== "yaml"
+```yaml
+cat <<EOF | kubectl apply -f -
+apiVersion: v1
+kind: ServiceAccount
+metadata:
+  name: hfserviceacc
+secrets:
+  - name: storage-config
+---
+apiVersion: serving.kserve.io/v1beta1
+kind: InferenceService
+metadata:
+  name: huggingface-llama3
+spec:
+  predictor:
+    serviceAccountName: hfserviceacc  # Option 1 for authenticating with HF_TOKEN
+    model:
+      modelFormat:
+        name: huggingface
+      args:
+        - --model_name=llama3
+        - --model_dir=/mnt/models
+      storageUri: hf://meta-llama/meta-llama-3-8b-instruct
+      resources:
+        limits:
+          cpu: "6"
+          memory: 24Gi
+          nvidia.com/gpu: "1"
+        requests:
+          cpu: "6"
+          memory: 24Gi
+          nvidia.com/gpu: "1"
+EOF
+```
+
+### Option 2: Use Environment Variable with Secret Ref
+Create a Kubernete HF token and specify the HF token secret reference using environment variable in the `InferenceService` Spec.
+
+=== "yaml"
+```yaml
+cat <<EOF | kubectl apply -f -
+apiVersion: serving.kserve.io/v1beta1
+kind: InferenceService
+metadata:
+  name: huggingface-llama3
+spec:
+  predictor:
+    model:
+      modelFormat:
+        name: huggingface
+      args:
+        - --model_name=llama3
+        - --model_dir=/mnt/models
+      storageUri: hf://meta-llama/meta-llama-3-8b-instruct
+      resources:
+        limits:
+          cpu: "6"
+          memory: 24Gi
+          nvidia.com/gpu: "1"
+        requests:
+          cpu: "6"
+          memory: 24Gi
+          nvidia.com/gpu: "1"
+      env:
+        - name: HF_TOKEN  # Option 2 for authenticating with HF_TOKEN
+          valueFrom:
+            secretKeyRef:
+              name: hf-secret
+              key: HF_TOKEN
+              optional: false
+EOF
+```
+
+## Check the InferenceService status.
+
+```bash
+kubectl get inferenceservices huggingface-llama3
+```
+
+!!! success "Expected Output"
+
+    ```{ .bash .no-copy }
+    NAME                 URL                                                   READY   PREV   LATEST   PREVROLLEDOUTREVISION   LATESTREADYREVISION                          AGE
+    huggingface-llama3   http://huggingface-llama3.default.example.com         True           100                              huggingface-llama3-predictor-default-47q2g   7d23h
+    ```

mkdocs.yml

@@ -74,6 +74,7 @@ nav:
                 - URI: modelserving/storage/uri/uri.md
                 - CA Certificate: modelserving/certificate/kserve.md
                 - GCS: modelserving/storage/gcs/gcs.md
+                - Hugging Face: modelserving/storage/huggingface/hf.md
           - Model Explainability:
                 - Concept: modelserving/explainer/explainer.md
                 - TrustyAI Explainer: modelserving/explainer/trustyai/README.md