Total runs:
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Growth Rate:
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Sponsored by
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LiquidAI / LFM2.5-1.2B-Instruct-MLX-4bit
Model's Last Updated: January 07 2026
text-generation
Introduction of LFM2.5-1.2B-Instruct-MLX-4bit
Model Details of LFM2.5-1.2B-Instruct-MLX-4bit
Try LFM • Documentation • LEAP • Blog
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 .
Runs of LiquidAI LFM2.5-1.2B-Instruct-MLX-4bit on huggingface.co
1.4K
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More Information About LFM2.5-1.2B-Instruct-MLX-4bit huggingface.co Model
Url of LFM2.5-1.2B-Instruct-MLX-4bit
LFM2.5-1.2B-Instruct-MLX-4bit huggingface.co Url
Provider of LFM2.5-1.2B-Instruct-MLX-4bit huggingface.co
Other API from LiquidAI
Updated:September 23 2026
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