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README.md

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+---
+base_model: SWE-bench/SWE-agent-LM-32B
+datasets:
+- SWE-bench/SWE-smith
+language:
+- en
+library_name: transformers
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- agent
+- software engineering
+- mlx
+- mlx-my-repo
+---
+
+# Felladrin/SWE-agent-LM-32B-mlx-4Bit
+
+The Model [Felladrin/SWE-agent-LM-32B-mlx-4Bit](https://huggingface.co/Felladrin/SWE-agent-LM-32B-mlx-4Bit) was converted to MLX format from [SWE-bench/SWE-agent-LM-32B](https://huggingface.co/SWE-bench/SWE-agent-LM-32B) using mlx-lm version **0.22.3**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("Felladrin/SWE-agent-LM-32B-mlx-4Bit")
+
+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)
+```