Instructions to use AnalyticsIntelligence/PIDGIN_gemma3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnalyticsIntelligence/PIDGIN_gemma3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AnalyticsIntelligence/PIDGIN_gemma3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from AnalyticsIntelligence/PIDGIN_gemma3: direct link, hf CLI and curl.
- Browser
- Download file 734 Bytes
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https://huggingface.co/AnalyticsIntelligence/PIDGIN_gemma3/resolve/main/README.md
- Command line
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hf download hf://AnalyticsIntelligence/PIDGIN_gemma3/README.md
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curl -L -o README.md https://huggingface.co/AnalyticsIntelligence/PIDGIN_gemma3/resolve/main/README.md
734 Bytes
| base_model: unsloth/gemma-3-4b-it-unsloth-bnb-4bit | |
| tags: | |
| - text-generation-inference | |
| - transformers | |
| - unsloth | |
| - gemma3 | |
| - trl | |
| license: apache-2.0 | |
| language: | |
| - en | |
| datasets: | |
| - Ephraimmm/pidgin_1 | |
| # Uploaded model | |
| This is a Pidgin Language model trained on pair to pair conversation in Pidgin. | |
| This is the 0.3 version | |
| - **Developed by:** Ephraimmm | |
| - **License:** apache-2.0 | |
| - **Finetuned from model :** unsloth/gemma-3-4b-it-unsloth-bnb-4bit | |
| This gemma3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. | |
| [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |