---
license: mit
language:
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- llama
- historical
- causal-lm
- mlx
- mlx-my-repo
base_model: haykgrigorian/TimeCapsuleLLM-v2-1800-1875
---

# FractalSurfer/TimeCapsuleLLM-v2-1800-1875-mlx-fp16

The Model [FractalSurfer/TimeCapsuleLLM-v2-1800-1875-mlx-fp16](https://huggingface.co/FractalSurfer/TimeCapsuleLLM-v2-1800-1875-mlx-fp16) was converted to MLX format from [haykgrigorian/TimeCapsuleLLM-v2-1800-1875](https://huggingface.co/haykgrigorian/TimeCapsuleLLM-v2-1800-1875) using mlx-lm version **0.29.1**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("FractalSurfer/TimeCapsuleLLM-v2-1800-1875-mlx-fp16")

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)
```