Reinforcement Learning
Transformers
Safetensors
English
qwen2
text-generation
text-generation-inference
unsloth
trl
grpo
thinkstation-pgx
gb10
Instructions to use ikedachin/qwen_finetune_16bit_unsloth_gb10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikedachin/qwen_finetune_16bit_unsloth_gb10 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ikedachin/qwen_finetune_16bit_unsloth_gb10") model = AutoModelForCausalLM.from_pretrained("ikedachin/qwen_finetune_16bit_unsloth_gb10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use ikedachin/qwen_finetune_16bit_unsloth_gb10 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ikedachin/qwen_finetune_16bit_unsloth_gb10 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for ikedachin/qwen_finetune_16bit_unsloth_gb10 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ikedachin/qwen_finetune_16bit_unsloth_gb10 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ikedachin/qwen_finetune_16bit_unsloth_gb10", max_seq_length=2048, )
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* Training was performed on a **ThinkStation PGX** workstation.
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* Built upon the [Qwen 2.5](https://huggingface.co/Qwen) architecture.
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## Training Infrastructure (ThinkStation PGX)
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```
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* Training was performed on a **ThinkStation PGX** workstation.
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* Built upon the [Qwen 2.5](https://huggingface.co/Qwen) architecture.
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## Purpose of this Project
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This model is a byproduct of **environment verification**.
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I aimed to confirm that the **ThinkStation PGX** can handle the heavy computation required for GRPO (Group Relative Policy Optimization).
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For the detailed verification process and hardware setup, please see my **[Qiita article(Japanese Only)](https://qiita.com/ikedachin/items/ac9dfd2e3597ebe1f306)**.
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```
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