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--- |
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base_model: zai-org/GLM-4.6V-Flash |
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library_name: transformers |
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model_name: GLM-4.6V-FDM |
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tags: |
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- generated_from_trainer |
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- sft |
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- trl |
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licence: license |
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--- |
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# Model Card for GLM-4.6V-FDM |
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This model is a fine-tuned version of [zai-org/GLM-4.6V-Flash](https://huggingface.co/zai-org/GLM-4.6V-Flash). |
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It has been trained using [TRL](https://github.com/huggingface/trl). |
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## Quick start |
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```python |
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from transformers import pipeline |
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" |
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generator = pipeline("text-generation", model="Melba/GLM-4.6V-FDM", device="cuda") |
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] |
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print(output["generated_text"]) |
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``` |
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## Training procedure |
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This model was trained with SFT. |
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### Framework versions |
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- TRL: 0.28.0.dev0 |
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- Transformers: 5.0.0rc0 |
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- Pytorch: 2.9.0+cu126 |
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- Datasets: 4.0.0 |
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- Tokenizers: 0.22.2 |
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## Citations |
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Cite TRL as: |
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```bibtex |
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@software{vonwerra2020trl, |
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title = {{TRL: Transformers Reinforcement Learning}}, |
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin}, |
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license = {Apache-2.0}, |
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url = {https://github.com/huggingface/trl}, |
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year = {2020} |
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} |
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``` |
