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LFM2.5-1.2B-Instruct-MLX-4bit
LiquidAI/LFM2.5-1.2B-Instruct-MLX-4bit
LFM2.5-1.2B-Instruct-MLX-4bit is a text generation model from LiquidAI. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as other.
<div align="center" <img src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png" alt="Liquid AI" style="width: 100%; max-width: 100%; height: auto; display: inlin…
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1.2B
659 MB on disk
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16
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.safetensors659 MB · 99%
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How the weights are stored.
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Model card
From the Hugging Face model README
<div align="center">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
alt="Liquid AI"
style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
<div style="display: flex; justify-content: center; gap: 0.5em; margin-bottom: 1em;">
<a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> •
<a href="https://docs.liquid.ai/lfm"><strong>Documentation</strong></a> •
<a href="https://leap.liquid.ai/"><strong>LEAP</strong></a>
</div>
</div>
LFM2.5-1.2B-Instruct-4bit
MLX export of LFM2.5-1.2B-Instruct for Apple Silicon inference.
Model Details
| Property | Value |
|---|---|
| Parameters | 1.2B |
| Precision | 4-bit |
| Group Size | 64 |
| Size | 628 MB |
| Context Length | 128K |
Recommended Sampling Parameters
| Parameter | Value |
|---|---|
| temperature | 0.1 |
| top_k | 50 |
| top_p | 0.1 |
| repetition_penalty | 1.05 |
| max_tokens | 512 |
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
from mlx_lm.sample_utils import make_sampler, make_logits_processors
model, tokenizer = load("LiquidAI/LFM2.5-1.2B-Instruct-4bit")
prompt = "What is the capital of France?"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
sampler = make_sampler(temp=0.1, top_k=50, top_p=0.1)
logits_processors = make_logits_processors(repetition_penalty=1.05)
response = generate(
model,
tokenizer,
prompt=prompt,
max_tokens=512,
sampler=sampler,
logits_processors=logits_processors,
verbose=True,
)
License
This model is released under the LFM 1.0 License.
- Task
- Text Generation
- Library
- mlx
- Type
- lfm2
- License
- other
- Languages
- en, ja, ko, fr, es, de
- Created
- Jan 6, 2026
- Updated
- Aug 12, 2026