Text Classification
Transformers
Safetensors
English
text-generation-inference
trl
qwen
wsd
ambiguity
Instructions to use deshanksuman/finetunedQwen3-4B-Instruct-WSD-Advanced-reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deshanksuman/finetunedQwen3-4B-Instruct-WSD-Advanced-reasoning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="deshanksuman/finetunedQwen3-4B-Instruct-WSD-Advanced-reasoning")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("deshanksuman/finetunedQwen3-4B-Instruct-WSD-Advanced-reasoning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,320 Bytes
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base_model:
- Qwen/Qwen3-4B
tags:
- text-generation-inference
- transformers
- trl
- qwen
- wsd
- ambiguity
license: apache-2.0
language:
- en
datasets:
- deshanksuman/Reasoning_WSD_dataset
pipeline_tag: text-classification
---
# Uploaded model
- **Developed by:** deshanksuman
- **License:** apache-2.0
- **Finetuned from model :** Qwen/Qwen3-4B
# Dataset
Fews Training data arranged in the format of Instruction, Input and output with advanced Reasonining for sense identification.
The data generation has been semi automated using the Arcee models.
The data has been validated by the human for it's structure and the correctnes.
The data source can be accessed here:
deshanksuman/Reasoning_WSD_dataset
# Hyperparameter for Training
- per_device_train_batch_size=4,
- gradient_accumulation_steps=8,
- warmup_steps=50,
- num_train_epochs=2,
- learning_rate=2e-4,
- fp16=not torch.cuda.is_bf16_supported(),
- bf16=torch.cuda.is_bf16_supported(),
- logging_steps=10,
- optim="adamw_torch",
- weight_decay=0.01,
- lr_scheduler_type="linear",
- seed=3407
This is developed by Deshan Sumanathilaka https://sumanathilaka.github.io
# Acknowledgement
We acknowledge the support of the Supercomputing Wales project, which is part-funded by the European Regional Development Fund (ERDF) via Welsh Government. |