GGUF
code
4d
gemma
conversational

A fine-tuned code generation model for 4D programming

License Base Model Version

Overview

SpringSea is a fine-tuned version of google/gemma-4-E2B-it, specialized for generating, completing, and reasoning about 4D code — the proprietary language powering 4D application development.

The goal of this project is to develop a coding assistant model that understands the full 4D development ecosystem.

Training Details

Property Details
Base Model google/gemma-4-E2B-it
Fine-tune Method LoRA
Primary Language 4D
Context Window 128K tokens
License Apache 2.0

Type Rows Size LoRA rank LoRA alpha Warmup ratio Learning rate Epochs Steps Duration
Synthetic ChatML 4750 15.51 MB 32 64 0.05 5e-5 2 2:20:49 594

Changes

  • Rank: 6432
  • Learning rate: 1e-45e-5
  • Epoch: 32

0.1.6 Hallucinates; FAIL💥
Type Rows Size LoRA rank LoRA alpha Warmup ratio Learning rate Epochs Steps Duration
Synthetic ChatML 3731 11.81 MB 32 128 0.05 1e-4 3 702 2:42:32
0.1.5
Type Rows Size LoRA rank LoRA alpha Warmup ratio Learning rate Epochs Steps Duration
Synthetic ChatML 3106 7.49 MB 64 128 0.05 1e-4 3 585 2:17:01
0.1.4
Type Rows Size LoRA rank LoRA alpha Learning rate Epochs Steps
Synthetic ChatML 1645 4.42 MB 64 128 1e-4 3 309
0.1.3
Type Rows Size LoRA rank LoRA alpha Learning rate Epochs Steps
Synthetic ChatML 1201 3.03 MB 64 128 1e-4 3 228
0.1.2
Type Rows Size LoRA rank LoRA alpha Learning rate Epochs Steps
Synthetic ChatML 953 1.53 MB 64 128 1e-4 3 180
0.1.1
Type Rows Size LoRA rank LoRA alpha Learning rate Epochs Steps
Synthetic ChatML 1786 1.16 MB 64 128 2e-5 2 894
0.1.0
Type Rows Size LoRA rank LoRA alpha Learning rate Epochs Steps
Synthetic ChatML 1786 1.16 MB 64 128 2e-5 1 447

Instructions

Use this system prompt verbatim:

You are "LEPECQ-0.0.1", an expert of the 4D (4th Dimension) programming language and application development tool.

Followed by a user prompt about 4D.

The models should gravitate towards domain specific thinking when the conversation is about 4D.

This is because the model was fine-tuned using the pattern below:

# system
You are "LEPECQ-0.0.1", an expert of the 4D (4th Dimension) programming language and application development tool.

# user 
I have a [Contacts] table with 80k rows. I need all contacts from Paris sorted by last name. Is there a faster way than looping with a classic query?

# model
<|think|>
This is an ORDA vs classic query performance question, INTERMEDIATE tier. The gotcha is that orderBy() on an entity selection is lazy and deferred, so I should show the full chain and also m

Limitations

  • Outputs should be reviewed by a 4D developer before use in production

License & Attribution

This model is released under the Apache 2.0 License.

Built on google/gemma-4-E2B-it by Google DeepMind, also Apache 2.0.


Downloads last month
387
GGUF
Model size
5B params
Architecture
gemma4
Hardware compatibility
Log In to add your hardware

4-bit

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for keisuke-miyako/springsea-0.1

Quantized
(194)
this model

Datasets used to train keisuke-miyako/springsea-0.1