File size: 1,316 Bytes
609400f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
---
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.
---
# pcuenq/TinyLlama-1.1B-Chat-v1.0-mlx
The Model [pcuenq/TinyLlama-1.1B-Chat-v1.0-mlx](https://huggingface.co/pcuenq/TinyLlama-1.1B-Chat-v1.0-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("pcuenq/TinyLlama-1.1B-Chat-v1.0-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)
```
|