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--- |
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library_name: transformers |
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license: gemma |
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datasets: |
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- haesleinhuepf/bio-image-analysis-qa |
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--- |
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# Model Card for Model ID |
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This is a proof-of-concept model. It is not properly trained. Do not use it for anything. |
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Gemma is provided under and subject to the Gemma Terms of Use found at [ai.google.dev/gemma/terms](https://ai.google.dev/gemma/terms/) |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** [More Information Needed] |
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- **Funded by [optional]:** [More Information Needed] |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** [More Information Needed] |
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- **License:** gemma license |
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- **Finetuned from model [optional]:** google/gemma-2b-it |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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``` |
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def prompt_hf(request, model="haesleinhuepf/gemma-2b-it-bia-proof-of-concept2"): |
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global prompt_hf |
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import transformers |
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import torch |
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if prompt_hf._pipeline is None: |
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prompt_hf._pipeline = transformers.pipeline( |
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"text-generation", model=model, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto" |
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) |
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return prompt_hf._pipeline(request)[0]['generated_text'] |
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prompt_hf._pipeline = None |
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prompt_hf("What is the capital of France?") |
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``` |
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## Training Details |
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### Training Data |
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https://huggingface.co/datasets/haesleinhuepf/bio-image-analysis-qa |
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## Model Card Contact |
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robert dot haase at uni minus leipzig dot de |
