Created model care

README.md

@@ -1,199 +1,101 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- medical
+license: mit
+datasets:
+- ekrombouts/Gardenia_instruct_dataset
+- ekrombouts/Olympia_SAMPC_dataset
+language:
+- nl
+base_model:
+- BramVanroy/fietje-2-instruct
 ---
 
 # Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
+This model is a fine-tuned version of bramvanrooy/fietje-2, designed to generate responses based on nursing home reports.
 
 ## Model Details
+- **Developed by:** Eva Rombouts
+- **Model type:** Causal Language Model
+- **Language(s) (NLP):** Dutch
+- **License:** MIT
+- **Finetuned from model [optional]:** BramVanroy/fietje-2-instruct
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+### Model Sources
+- **Repository:** https://github.com/ekrombouts/gcai_zuster_fietje
 
 ## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
+Generating summaries and responses based on nursing home reports.
 
 ### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+Not suitable for generating medical advice or any other critical decision-making processes.
 
 ## Bias, Risks, and Limitations
+The model may generate biased or inaccurate responses. Users should verify the generated content.
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+## How to Get Started with the Model
+Use the code below to get started with the model.
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-### Recommendations
+model_id = "ekrombouts/zuster_fietje"
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+model = AutoModelForCausalLM.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+prompt = """Rapportages:
+Mw was vanmorgen incontinent van urine, bed was ook nat. Mw is volledig verzorgd, bed is verschoond,
+Mw. haar kledingkast is opgeruimd.
+Mw. zei:"oooh kind, ik heb zo'n pijn. Mijn benen. Dat gaat nooit meer weg." Mw. zat in haar rolstoel en haar gezicht trok weg van de pijn en kreeg traanogen. Mw. werkte goed mee tijdens adl. en was vriendelijk aanwezig. Pijn. Mw. kreeg haar medicatie in de ochtend, waaronder pijnstillers. 1 uur later adl. gegeven.
+Mevr. in de ochtend ondersteund met wassen en aankleden. Mevr was rustig aanwezig.
+Mw is volledig geholpen met ochtendzorg, mw haar haren zijn gewassen. Mw haar nagels zijn kort geknipt.
+Mevr heeft het ontbijt op bed genuttigd. Daarna mocht ik na de tweede poging Mevr ondersteunen met wassen en aankleden.
 
-## How to Get Started with the Model
+Instructie:
+Beschrijf de lichamelijke klachten
 
-Use the code below to get started with the model.
-
-[More Information Needed]
+Antwoord:
+"""
 
+input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+output = model.generate(input_ids)
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
 ## Training Details
-
 ### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
+- ekrombouts/Gardenia_instruct_dataset
+- ekrombouts/Olympia_SAMPC_dataset
 
 ### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
 #### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
+- **Training regime:** fp16 mixed precision
 
 ## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
+Evaluated on a subset of nursing home reports.
 
 #### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
+Qualitative assessment of generated responses.
 
 ### Results
 
 [More Information Needed]
 
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
 ## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+- **Hardware Type:** GPU (NVIDIA A100)
+- **Hours used:** 8 hours
+- **Cloud Provider:** Google 
+- **Compute Region:** europe-west4 
+- **Carbon Emitted:** 54 kg CO2 eq.
 
 **BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+```bibtex
+@misc{zuster_fietje,
+  author = {Eva Rombouts},
+  title = {Zuster Fietje: A Fine-Tuned Model for Nursing Home Reports},
+  year = {2024},
+  url = {https://huggingface.co/ekrombouts/zuster_fietje},
+}```