Create README.md

README.md

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+---
+license: mit
+---
+This uv-script allows you to run batch inference on vllm over an hf dataset as long as it has a messages column. 
+
+Use though code
+```python
+#!/usr/bin/env python3
+from dotenv import load_dotenv
+from huggingface_hub import HfApi
+
+load_dotenv()
+
+import os
+
+DATASET_REPO_ID = "tytodd/test-job-dataset"
+SCRIPT_URL = "https://huggingface.co/datasets/modaic/batch-vllm/raw/main/generate_responses.py"
+
+
+def main() -> None:
+    api = HfApi()
+    job_info = api.run_uv_job(
+        SCRIPT_URL,
+        script_args=[
+            DATASET_REPO_ID,
+            DATASET_REPO_ID,
+            "--model-id",
+            # "Qwen/Qwen3-235B-A22B-Instruct-2507",
+            "deepseek-ai/DeepSeek-V3.2",
+            # "zai-org/GLM-5", # transformers > 5
+            # "moonshotai/Kimi-K2.5",
+            "--messages-column",
+            "messages",
+        ],
+        dependencies=["transformers<5"],
+        image="vllm/vllm-openai:latest",
+        flavor="h200x4",
+        secrets={"HF_TOKEN": os.getenv("HF_TOKEN")},
+    )
+    print(f"Created job {job_info.id}")
+    print(job_info.url)
+
+
+if __name__ == "__main__":
+    main()
+```
+
+or in cli
+
+```
+uvx hf jobs uv run \
+    --flavor l4x4 \
+    --secrets HF_TOKEN \
+    https://huggingface.co/datasets/modaic/batch-vllm/resolve/main/generate_responses.py \
+    username/input-dataset \
+    username/output-dataset \
+    --messages-column messages \
+    --model-id Qwen/Qwen3-30B-A3B-Instruct-2507 \
+    --temperature 0.7 \
+    --max-tokens 16384
+```