Add vLLM info and config

README.md

@@ -137,6 +137,38 @@ print(scores.tolist())
 
 ```
 
+#### vLLM Usage
+
+1. Ensure you are using `vllm==0.11.0`.
+2. Clone [this model's repository](https://huggingface.co/nvidia/llama-nemotron-embed-1b-v2/tree/main). Overwrite `config.json` with `config_vllm.json`.
+3. Start the vLLM server with the following command (replace the `<path_to_the_cloned_repository>` and `<num_gpus_to_use>` with your values):
+```
+vllm serve \
+    <path_to_the_cloned_repository> \
+    --trust-remote-code \
+    --runner pooling \
+    --model-impl vllm \
+    --override-pooler-config '{\"pooling_type\": \"MEAN\"}' \
+    --data-parallel-size <num_gpus_to_use> \
+    --dtype float32 \
+    --port 8000
+```
+
+You can now access the model using the OpenAI sdk, for instance:
+
+```
+from openai import OpenAI
+client = OpenAI(base_url="http://localhost:8000/v1")
+models = client.models.list()
+model_name = models.data[0].id
+
+response = client.embeddings.create(
+    input=['query: how much protein should a female eat'],
+    model=model_name
+)
+response.data[0].embedding
+```
+
 ### **Software Integration**
 
 **Runtime Engine:** Llama Nemotron embedding NIM

config_vllm.json

@@ -0,0 +1,38 @@
+{
+  "_name_or_path": "nvidia/llama-3.2-nv-embedqa-1b-v2",
+  "architectures": [
+    "LlamaModel"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "is_causal": false,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pooling": "avg",
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}