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  # Grok 2
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  This repository contains the weights of Grok 2, a model trained and used at xAI in 2024.
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- ## Usage: Serving with SGLang
 
 
 
 
 
 
 
 
 
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- - Download the weights. You can replace `/local/grok-2` with any other folder name you prefer.
 
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- ```
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- hf download xai-org/grok-2 --local-dir /local/grok-2
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- ```
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- You might encounter some errors during the download. Please retry until the download is successful.
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- If the download succeeds, the folder should contain **42 files** and be approximately 500 GB.
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- - Launch a server.
 
 
 
 
 
 
 
 
 
 
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- Install the latest SGLang inference engine (>= v0.5.1) from https://github.com/sgl-project/sglang/
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- Use the command below to launch an inference server. This checkpoint is TP=8, so you will need 8 GPUs (each with > 40GB of memory).
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- ```
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- python3 -m sglang.launch_server --model /local/grok-2 --tokenizer-path /local/grok-2/tokenizer.tok.json --tp 8 --quantization fp8 --attention-backend triton
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- ```
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- - Send a request.
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- This is a post-trained model, so please use the correct [chat template](https://github.com/sgl-project/sglang/blob/97a38ee85ba62e268bde6388f1bf8edfe2ca9d76/python/sglang/srt/tokenizer/tiktoken_tokenizer.py#L106).
 
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- ```
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- python3 -m sglang.test.send_one --prompt "Human: What is your name?<|separator|>\n\nAssistant:"
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- ```
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- You should be able to see the model output its name, Grok.
 
 
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- Learn more about other ways to send requests [here](https://docs.sglang.ai/basic_usage/send_request.html).
 
 
 
 
 
 
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  ## License
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- The weights are licensed under the [Grok 2 Community License Agreement](https://huggingface.co/xai-org/grok-2/blob/main/LICENSE).
 
 
 
 
 
 
 
 
 
 
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+ language:
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+
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+ - en
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+ license: other
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+ library_name: sglang
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+ pipeline_tag: text-generation
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+ tags:
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+ - grok-2
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+ - xai
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+ - sglang
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+ - inference
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+ - triton
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+ base_model: xai-org/grok-2
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+ model-index:
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+ - name: grok-2
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+ results: []
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+
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  # Grok 2
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  This repository contains the weights of Grok 2, a model trained and used at xAI in 2024.
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+ - License: Grok 2 Community License Agreement (./LICENSE)
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+ - Ownership: xAI (this document does not change license or weights)
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+
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+ ## Weights
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+
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+ Download from the Hub (≈500 GB total; 42 files):
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+ hf download xai-org/grok-2 --local-dir /local/grok-2
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+ If you see transient errors, retry until it completes. On success, you should see 42 files (~500 GB).
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+
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+ ## Hardware and Parallelism
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+ - This checkpoint is configured for TP=8.
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+ - Recommended: 8× GPUs (each > 40 GB memory).
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+ ## Serving with SGLang (>= v0.5.1)
 
 
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+ Install SGLang from https://github.com/sgl-project/sglang/
 
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+ Launch an inference server:
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+ python3 -m sglang.launch_server \
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+ --model /local/grok-2 \
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+ --tokenizer-path /local/grok-2/tokenizer.tok.json \
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+ --tp 8 \
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+ --quantization fp8 \
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+ --attention-backend triton
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+ Send a test request (chat template aware):
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+ python3 -m sglang.test.send_one --prompt \
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+ "Human: What is your name?<|separator|>\n\nAssistant:"
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+ You should see the model respond with its name: “Grok”.
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+ More ways to send requests:
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+ - https://docs.sglang.ai/basic_usage/send_request.html
 
 
 
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+ Note: this is a post-trained model; use the correct chat template:
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+ - https://github.com/sgl-project/sglang/blob/97a38ee85ba62e268bde6388f1bf8edfe2ca9d76/python/sglang/srt/tokenizer/
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+ tiktoken_tokenizer.py#L106
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+ ## Community Usage (Examples)
 
 
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+ - Local-only serving behind VPN/Nginx allowlist
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+ - Log and audit inference (timestamps and SHA‑256 manifests)
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+ - Optional fallback to xAI’s API when local capacity is unavailable
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+ These examples describe usage patterns only; they do not alter license or weights.
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+
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+ ## Limitations and Safety
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+
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+ - Large memory footprint (multi-GPU recommended)
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+ - Follow the Grok 2 Community License
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+ - Redact any sensitive data before inference if routing via cloud services
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  ## License
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+ Weights are licensed under the Grok 2 Community License Agreement (./LICENSE).
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+
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+ تعليق PR مقترح (قصير ومحايد)
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+
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+ - Summary: Fix model card metadata (YAML at top), remove duplicated sections, fence code blocks, and keep license/ownership
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+ unchanged.
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+ - Scope: README.md only. No weights or license changes.
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+ - Rationale: Resolves Hub YAML warning and makes SGLang instructions copy‑paste runnable.
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+ - Notes: URLs unbroken; model-index.results properly nested.
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+