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LFM2-1.2B-Autoround-Safetensors
simaai/LFM2-1.2B-Autoround-Safetensors
LFM2-1.2B-Autoround-Safetensors is a text generation model from simaai. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Pre-LLiMa Hugging Face checkpoint for Sima.ai deployment experiments. It is based on LiquidAI/LFM2-1.2B at source revision 933cee00d754fb3bfe06c644c0cb95453f2d8bb2 and remains subject to that model's MIT license and l…
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Model card
From the Hugging Face model README
LFM2-1.2B Autoround
Pre-LLiMa Hugging Face checkpoint for Sima.ai deployment experiments. It is based on LiquidAI/LFM2-1.2B at source revision 933cee00d754fb3bfe06c644c0cb95453f2d8bb2 and remains subject to that model's MIT license and limitations.
Quantization
| Component | Method | Weight format | Details |
|---|---|---|---|
| Decoder Linear layers | AutoRound | symmetric INT4, G256 | 92 targets; lm_head excluded |
lm_head | GPTQ | symmetric INT4, G256 | static act-order, block size 128, dampening 0.01 |
| Mixed-precision exceptions | — | source dtype | Non-Linear parameters remain at source precision |
Calibration used HuggingFaceH4/ultrachat_200k, train_sft[:512], rendered with the source chat template. Token IDs were deterministically concatenated and packed into 512 full 1024-token spans, with no shuffle. AutoRound used 200 iterations and batch size 1.
Evaluation
Full wikitext-2-raw-v1 evaluation used the wikitext lm-eval task, no example limit, batch size 1, CUDA, and the same evaluator for both checkpoints on 2026-07-19.
| Checkpoint | Word perplexity | Status |
|---|---|---|
LiquidAI/LFM2-1.2B source | 34.597716 | Full run |
| This UltraChat checkpoint | 38.401202 | Full run |
| Absolute degradation | 3.803485 | Lower is better |
| Relative degradation | 10.993% | 100 * (quantized / source - 1) |
UltraChat is the selected calibration corpus because the intended deployment prioritizes instruction-following data. Finite quantization scales and a Transformers chat-generation smoke test both passed.
Reproduction
This directory contains the exact quantize.py, recipe.yaml, and versions.txt.
python quantize.py \
--model-path /project/mlasw/share/huggingface/models--LiquidAI--LFM2-1.2B \
--output-dir /path/to/output
Environment
Exact Python, CUDA, Torch, Transformers, llm-compressor, AutoRound, and
compressed-tensors versions are recorded in versions.txt.
Deployment
This is the pre-LLiMa quantized Hugging Face artifact. Compile it separately for the target Sima.ai platform and keep compiler output separate. No upload is authorized as part of the current local batch.
Limitations
WikiText perplexity measures language-model likelihood and does not directly measure instruction following. Quantization quality can vary with language, domain, prompt format, context length, safety requirements, and runtime. Validate the intended deployment workload independently.
- Task
- Text Generation
- Library
- transformers
- Type
- lfm2
- License
- mit
- Languages
- multilingual
- Created
- Jul 16, 2026
- Updated
- Sep 1, 2026