granite-claude-h-350m – AI Model by Avtrkrb | AlphaNeural AI

You can deploy this model and start earning money today!

Avtrkrb/
granite-claude-h-350m

like

0

granitemoehybrid

text-generation

chain-of-thought

Avtrkrb/combined-reasoning-claude

unsloth/granite-4.0-h-350m-unsloth-bnb-4bit

endpoints_compatible

Views

No views yet

granite-claude-h-350m

A reasoning-focused fine-tune of IBM Granite 4.0 H 350M.

This model was trained on the Avtrkrb/combined-reasoning-claude dataset using Unsloth and LoRA fine-tuning.

The objective of the fine-tuning process was to improve:

Multi-step reasoning
Instruction following
Logical problem solving
Structured thought processes
Explicit reasoning traces

Base Model

This model is derived from:

unsloth/granite-4.0-h-350m-unsloth-bnb-4bit

which itself is an Unsloth-optimized version of IBM Granite 4.0 H 350M.

Dataset

Training dataset:

https://huggingface.co/datasets/Avtrkrb/combined-reasoning-claude

The dataset contains instruction/response pairs focused on reasoning tasks.

Intended Use

This model is intended for:

Reasoning assistants
Educational applications
Small local inference deployments
Research experiments
Lightweight reasoning workloads

Limitations

This model is only 350M parameters.

Users should expect:

Reduced factual accuracy compared to larger models
Occasional reasoning failures
Hallucinations
Limited world knowledge

Outputs should be verified before use in high-stakes settings.

Example Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "Avtrkrb/granite-claude-h-350m"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

prompt = "Explain why the sky appears blue."

inputs = tokenizer(prompt, return_tensors="pt")

outputs = model.generate(
    **inputs,
    max_new_tokens=512,
)

print(tokenizer.decode(outputs[0]))

Training

Fine-tuned using:

Unsloth
LoRA
PEFT
Transformers

Acknowledgements

IBM Granite Team
Unsloth
Hugging Face

License

This repository follows the license of the underlying Granite model.