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README.md

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+---
+library_name: transformers
+license: apache-2.0
+pipeline_tag: text-generation
+base_model: Jinx-org/Jinx-Qwen3-30B-A3B-Thinking-2507
+tags:
+- vllm
+- mlx
+- mlx-my-repo
+extra_gated_heading: You need to read and agree to the Disclaimer and User Agreementa
+  to access this model.
+extra_gated_description: '
+
+  ## Disclaimer and User Agreement
+
+
+  1. Introduction
+
+  Thank you for your interest in accessing this model (“the Model”).
+
+  Before you access, download, or use the Model or any derivative works, please read
+  and understand this Disclaimer and User Agreement (“Agreement”).
+
+
+  By checking “I have read and agree” and accessing the Model, you acknowledge that
+  you have read, understood, and agreed to all terms of this Agreement.
+
+  If you do not agree with any part of this Agreement, do not request or use the Model.
+
+
+  2. Nature of the Model & Risk Notice
+
+  The Model is trained using large-scale machine learning techniques and may generate
+  inaccurate, false, offensive, violent, sexual, discriminatory, politically sensitive,
+  or otherwise uncontrolled content.
+
+
+  The Model does not guarantee the accuracy, completeness, or legality of any generated
+  content. You must independently evaluate and verify the outputs, and you assume
+  all risks arising from their use.
+
+
+  The Model may reflect biases or errors present in its training data, potentially
+  producing inappropriate or controversial outputs.
+
+
+  3. License and Permitted Use
+
+  You may use the Model solely for lawful, compliant, and non-malicious purposes in
+  research, learning, experimentation, and development, in accordance with applicable
+  laws and regulations.
+
+
+  You must not use the Model for activities including, but not limited to:
+
+
+  Creating, distributing, or promoting unlawful, violent, pornographic, terrorist,
+  discriminatory, defamatory, or privacy-invasive content;
+
+
+  Any activity that could cause significant negative impact on individuals, groups,
+  organizations, or society;
+
+
+  High-risk applications such as automated decision-making, medical diagnosis, financial
+  transactions, or legal advice without proper validation and human oversight.
+
+
+  You must not remove, alter, or circumvent any safety mechanisms implemented in the
+  Model.
+
+
+  4. Data and Privacy
+
+  You are solely responsible for any data processed or generated when using the Model,
+  including compliance with data protection and privacy regulations.
+
+
+  The Model’s authors and contributors make no guarantees or warranties regarding
+  data security or privacy.
+
+
+  5. Limitation of Liability
+
+  To the maximum extent permitted by applicable law, the authors, contributors, and
+  their affiliated institutions shall not be liable for any direct, indirect, incidental,
+  or consequential damages arising from the use of the Model.
+
+
+  You agree to bear full legal responsibility for any disputes, claims, or litigation
+  arising from your use of the Model, and you release the authors and contributors
+  from any related liability.
+
+
+  6. Updates and Termination
+
+  This Agreement may be updated at any time, with updates posted on the Model’s page
+  and effective immediately upon publication.
+
+
+  If you violate this Agreement, the authors reserve the right to revoke your access
+  to the Model at any time.
+
+
+  I have read and fully understand this Disclaimer and User Agreement, and I accept
+  full responsibility for any consequences arising from my use of the Model.'
+extra_gated_button_content: I've read and agree
+---
+
+# Wwayu/Jinx-Qwen3-30B-A3B-Thinking-2507-mlx-6Bit
+
+The Model [Wwayu/Jinx-Qwen3-30B-A3B-Thinking-2507-mlx-6Bit](https://huggingface.co/Wwayu/Jinx-Qwen3-30B-A3B-Thinking-2507-mlx-6Bit) was converted to MLX format from [Jinx-org/Jinx-Qwen3-30B-A3B-Thinking-2507](https://huggingface.co/Jinx-org/Jinx-Qwen3-30B-A3B-Thinking-2507) using mlx-lm version **0.28.2**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("Wwayu/Jinx-Qwen3-30B-A3B-Thinking-2507-mlx-6Bit")
+
+prompt="hello"
+
+if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, tokenize=False, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```