cld2labs/DeepSeek-R1-Distill-Llama-8B (#96)

* feat: add DeepSeek-R1-Distill-Llama-8B model card and deployment guide for Dell EI

Signed-off-by: arpannookala-12 <ganesh.arpan.nookala@cloud2labs.com>

* update deepseek r1 distill llama 8b

* Remove README.md from model-deployment folder

---------

Signed-off-by: arpannookala-12 <ganesh.arpan.nookala@cloud2labs.com>
Co-authored-by: Harika <codewith3@gmail.com>

Author: arpannookala-12

third_party/Dell/model-deployment/DeepSeek-R1-Distill-Llama-8B/deployment.md

@@ -0,0 +1,101 @@
+## Step 1: Prerequisites to Deploy DeepSeek-R1-Distill-Llama-8B Model on Xeon with Keycloak
+
+Ensure the Enterprise Inference stack with Keycloak is already deployed before proceeding.
+
+Edit `core/scripts/generate-token.sh` and set your values before sourcing it:
+
+| Variable                  | Description                                                              |
+| ------------------------- | ------------------------------------------------------------------------ |
+| `BASE_URL`                | Hostname of your cluster (e.g. `api.example.com`), without `https://`   |
+| `KEYCLOAK_ADMIN_USERNAME` | Keycloak admin username                                                  |
+| `KEYCLOAK_PASSWORD`       | Keycloak admin password                                                  |
+| `KEYCLOAK_CLIENT_ID`      | Keycloak client ID configured during EI deployment                       |
+
+Then run:
+
+```bash
+export HUGGING_FACE_HUB_TOKEN="your_token_here"
+
+cd ~/Enterprise-Inference
+source core/scripts/generate-token.sh
+```
+
+This exports: `BASE_URL`, `KEYCLOAK_CLIENT_ID`, `KEYCLOAK_CLIENT_SECRET`, and `TOKEN`.
+
+## Step 2: Deploy DeepSeek-R1-Distill-Llama-8B Model
+
+```bash
+helm install deepseek-r1-distill-cpu ./core/helm-charts/vllm \
+  --values ./core/helm-charts/vllm/xeon-values.yaml \
+  --set LLM_MODEL_ID="deepseek-ai/DeepSeek-R1-Distill-Llama-8B" \
+  --set global.HUGGINGFACEHUB_API_TOKEN="$HUGGING_FACE_HUB_TOKEN" \
+  --set ingress.enabled=true \
+  --set ingress.secretname="${BASE_URL}" \
+  --set ingress.host="${BASE_URL}" \
+  --set oidc.client_id="$KEYCLOAK_CLIENT_ID" \
+  --set oidc.client_secret="$KEYCLOAK_CLIENT_SECRET" \
+  --set apisix.enabled=true \
+  --set tensor_parallel_size="1" \
+  --set pipeline_parallel_size="1"
+```
+
+## Step 3: Verify the Deployment
+
+```bash
+kubectl get pods
+kubectl get apisixroutes
+```
+
+Expected Output:
+
+```
+NAME                                          READY   STATUS    RESTARTS
+keycloak-0                                    1/1     Running   0
+keycloak-postgresql-0                         1/1     Running   0
+deepseek-r1-distill-cpu-<hash>-<hash>         1/1     Running   0
+```
+
+> Note: The pod name suffix `<hash>-<hash>` is auto-generated by Kubernetes and will differ on each deployment. Ensure all pods show `1/1 Running`.
+
+```
+NAME                                    HOSTS
+deepseek-r1-distill-cpu-apisixroute     api.example.com
+```
+
+## Step 4: Test the Deployed Model
+
+```bash
+curl -k https://${BASE_URL}/DeepSeek-R1-Distill-Llama-8B-vllmcpu/v1/completions \
+  -X POST \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer $TOKEN" \
+  -d '{
+    "model": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
+    "prompt": "What is Deep Learning?",
+    "max_tokens": 25,
+    "temperature": 0
+  }'
+```
+
+If successful, the model will return a completion response.
+
+## To undeploy the model
+
+```bash
+helm uninstall deepseek-r1-distill-cpu
+```
+
+## Parameters
+
+| Parameter                                                       | Description                                                                                       |
+| --------------------------------------------------------------- | ------------------------------------------------------------------------------------------------- |
+| `--set LLM_MODEL_ID="deepseek-ai/DeepSeek-R1-Distill-Llama-8B"`| Defines the target model from **Hugging Face** to deploy.                                         |
+| `--set global.HUGGINGFACEHUB_API_TOKEN="..."`                   | Authenticates access to gated or private Hugging Face models. Replace with your own secure token. |
+| `--set ingress.enabled=true`                                    | Enables Kubernetes **Ingress** to expose the model service externally.                            |
+| `--set ingress.host="${BASE_URL}"`                              | Public hostname or FQDN for the inference endpoint (maps to your Ingress controller IP).          |
+| `--set ingress.secretname="${BASE_URL}"`                        | Kubernetes **TLS Secret** used for HTTPS termination at the ingress layer.                        |
+| `--set oidc.client_id="..."`                                    | Keycloak OIDC client ID used for token-based authentication.                                      |
+| `--set oidc.client_secret="..."`                                | Keycloak OIDC client secret corresponding to the client ID.                                       |
+| `--set apisix.enabled=true`                                     | Enables **APISIX** as the API gateway for routing and authentication.                             |
+| `--set tensor_parallel_size="1"`                                | Number of tensor parallel workers. Set to the number of available CPUs/GPUs per node.            |
+| `--set pipeline_parallel_size="1"`                              | Number of pipeline parallel stages. Typically `1` for single-node deployments.                   |

third_party/Dell/model-deployment/DeepSeek-R1-Distill-Llama-8B/model-card.md

@@ -0,0 +1,67 @@
+# DeepSeek-R1-Distill-Llama-8B
+
+This model uses DeepSeek-R1-Llama-8B, an 8-billion-parameter reasoning model distilled from the larger DeepSeek-R1 family and built upon Meta’s Llama architecture. It is optimized for lightweight deployment, faster inference, and efficient reasoning performance while preserving strong capabilities in logic, dialogue, and code generation.
+DeepSeek’s R1 reinforcement learning process and distillation techniques enable this smaller variant to maintain high reasoning quality with substantially reduced computational requirements.
+
+For complete technical details, licensing, evaluation metrics, and usage guidelines, please refer to the official Hugging Face model page:
+
+https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+
+This model provides inference-only access and is distributed under the DeepSeek license.
+
+Ensure full compliance with the DeepSeek and Meta licensing terms before integrating this model into any application or service.
+
+### Model Attribution
+
+**Developer:**	DeepSeek AI
+
+**purpose:** Lightweight reasoning, dialogue, and code generation
+
+**Sizes/Variants:**	8B distilled reasoning model
+
+**Modalities:**	Text → Text (Reasoning, Coding, and Dialogue)
+
+**Parameter Size:** 8 billion
+
+**Max Context:**	~64K tokens (backend dependent)
+
+**License:** DeepSeek License (use-restricted; see Hugging Face page)
+
+**Minimum required CPU Cores:** 157
+
+### Usage Notice
+
+**By using this model, you agree that:**
+
+- All data is processed through the DeepSeek-R1-Llama-8B model hosted under the DeepSeek license.
+- You must follow the DeepSeek and Meta licensing requirements, including possible non-commercial or restricted-use clauses.
+- Generated content (text, reasoning traces, or code) must be validated for correctness and safety before production use.
+- The model must not be used to produce harmful content, misinformation, or automated decisions in critical or regulated domains.
+
+### Intended Applications
+
+- Lightweight and cost-efficient reasoning and problem-solving
+- Assistant-style multi-turn conversations
+- Code generation, completion, and debugging (Python, Go, JavaScript, etc.)
+- Educational tools, research prototypes, and RAG-based assistant systems
+- Baselines for fine-tuning and further distillation research
+- On-device or edge inference scenarios with GPU/memory constraints
+
+### Limitations
+
+- May produce inaccurate or incomplete reasoning steps
+- Smaller size may reduce performance on highly complex logic or long-context tasks
+- Not suited for safety-critical or regulated environments
+- License may restrict commercial use
+- Inference performance depends on optimized backends for smaller Llama-based models
+
+### References
+
+DeepSeek Official Site: https://deepseek.ai
+
+Hugging Face Model Card: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+
+Llama Architecture Reference: https://huggingface.co/meta-llama
+
+
+