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README.md

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+---
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
+datasets:
+- cerebras/SlimPajama-627B
+- bigcode/starcoderdata
+- HuggingFaceH4/ultrachat_200k
+- HuggingFaceH4/ultrafeedback_binarized
+language:
+- en
+license: apache-2.0
+tags:
+- mlx
+widget:
+- example_title: Fibonacci (Python)
+  messages:
+  - role: system
+    content: You are a chatbot who can help code!
+  - role: user
+    content: Write me a function to calculate the first 10 digits of the fibonacci
+      sequence in Python and print it out to the CLI.
+---
+
+# reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-mlx
+
+The Model [reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-mlx](https://huggingface.co/reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-mlx) was converted to MLX format from [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) using mlx-lm version **0.19.1**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("reach-vb/TinyLlama-1.1B-Chat-v1.0-Q4-mlx")
+
+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)
+```