Modelpublic

reallexi/lexi-coder-v4.2

sourceHugging Faceotherupdated 2mo agoView on Hugging Face

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Model Card

lexi-coder-v4.2

A standalone model of 3.85B parameters, derived from `microsoft/Phi-4-mini-instruct`.

The adapter has been merged into the base weights, so no PEFT adapter is needed at runtime.

Size and requirements


Parameters	3,847,556,096 (3.85B)
Weights on disk	7.15 GB
Trained context length	2,048 tokens
Base model	`microsoft/Phi-4-mini-instruct`

Approximate memory to hold the weights. Add context and runtime overhead on top.

Precision	Weights
FP16 / BF16	7.17 GB
8-bit (Q8_0)	3.58 GB
4-bit (Q4KM)	1.97 GB

Training


Strategy	lora
Adapter	Auto LoRA
LoRA rank / alpha	16 / 32
Dataset	`ianncity/GLM-5.2-Conversation`
Samples learned	50,296 (through phase 26 of 50)
Training steps	1,480
Epochs	5

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("lexi-coder-v4.2")
tokenizer = AutoTokenizer.from_pretrained("lexi-coder-v4.2")

License and attribution

The effective terms are inherited from the base model and the training data, which are not necessarily the same as this project's own license. Review both before redistributing.

—Base model: `microsoft/Phi-4-mini-instruct`

—Training data: ianncity/GLM-5.2-Conversation

Produced by Reallexi LLC AI Model Builder from training job #1562. Core: https://llm.reallexi.io

Keep reallexi-model.json, NOTICE, and all applicable upstream license files with the model.