Update README.md

README.md

@@ -1,13 +1,114 @@
 ---
 library_name: transformers
-tags: []
+license: cc-by-nc-4.0
+language:
+- multilingual
+- af
+- am
+- ar
+- as
+- azb
+- be
+- bg
+- bm
+- bn
+- bo
+- bs
+- ca
+- ceb
+- cs
+- cy
+- da
+- de
+- du
+- el
+- en
+- eo
+- es
+- et
+- eu
+- fa
+- fi
+- fr
+- ga
+- gd
+- gl
+- ha
+- hi
+- hr
+- ht
+- hu
+- id
+- ig
+- is
+- it
+- iw
+- ja
+- jv
+- ka
+- ki
+- kk
+- km
+- ko
+- la
+- lb
+- ln
+- lo
+- lt
+- lv
+- mi
+- mr
+- ms
+- mt
+- my
+- 'no'
+- oc
+- pa
+- pl
+- pt
+- qu
+- ro
+- ru
+- sa
+- sc
+- sd
+- sg
+- sk
+- sl
+- sm
+- so
+- sq
+- sr
+- ss
+- sv
+- sw
+- ta
+- te
+- th
+- ti
+- tl
+- tn
+- tpi
+- tr
+- ts
+- tw
+- uk
+- ur
+- uz
+- vi
+- war
+- wo
+- xh
+- yo
+- zh
+- zu
+base_model:
+- CohereForAI/aya-expanse-8b
+- timm/ViT-SO400M-14-SigLIP-384
+pipeline_tag: image-text-to-text
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
+# Centurio Aya
 
 ## Model Details
 
@@ -15,23 +116,19 @@ tags: []
 
 <!-- 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 type:** Centurio is an open-source multilingual large vision-language model.
+- **Training Data:** COMING SOON 
+- **Languages:** The model was trained with the following 100 languages: `af, am, ar, ar-eg, as, azb, be, bg, bm, bn, bo, bs, ca, ceb, cs, cy, da, de, du, el, en, eo, es, et, eu, fa, fi, fr, ga, gd, gl, ha, hi, hr, ht, hu, id, ig, is, it, iw, ja, jv, ka, ki, kk, km, ko, la, lb, ln, lo, lt, lv, mi, mr, ms, mt, my, no, oc, pa, pl, pt, qu, ro, ru, sa, sc, sd, sg, sk, sl, sm, so, sq, sr, ss, sv, sw, ta, te, th, ti, tl, tn, tpi, tr, ts, tw, uk, ur, uz, vi, war, wo, xh, yo, zh, zu
+`
+- **License:** This work is released under the Creative Commons Attribution Non Commercial 4.0 license. 
 
-### Model Sources [optional]
+### Model Sources 
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** []
+- **Paper:** []
+- **Demo:** []
 
 ## Uses
 
@@ -41,159 +138,106 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 <!-- 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]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## 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]
-
-### 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]
+The model can be used directly through the `transformers` library with our custom code. 
 
-[More Information Needed]
+```python
+from transformers import AutoModelForCausalLM, AutoProcessor
+import timm
+from PIL import Image    
+import requests
 
+url = "https://upload.wikimedia.org/wikipedia/commons/b/bd/Golden_Retriever_Dukedestiny01_drvd.jpg"
+image = Image.open(requests.get(url, stream=True).raw)
 
-#### Training Hyperparameters
+model_name = "WueNLP/centurio_aya"
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+processor = AutoProcessor.from_pretrained(model_name, trust_remote_code=True)
 
-#### Speeds, Sizes, Times [optional]
+## Appearance of images in the prompt are indicates with '<image_placeholder>'!
+prompt = "<image_placeholder>\nBriefly describe the image in German."
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+messages = [
+    {"role": "user", "content": prompt}
+]
 
-[More Information Needed]
+text = processor.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
 
-## Evaluation
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    trust_remote_code=True
+)
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+model_inputs = processor(text=[text], images=[image] return_tensors="pt").to(model.device)
 
-### Testing Data, Factors & Metrics
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=128
+)
 
-#### Testing Data
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
 
-<!-- This should link to a Dataset Card if possible. -->
+response = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
-[More Information Needed]
+```
 
-#### Factors
+#### Multiple Images
+We natively support multi-image inputs. You only have to 1) include more `<image_placeholder>` while 2) passing all images of the *entire batch* as a flat list:
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+```python
+[...]
+# Variables reused from above.
 
-[More Information Needed]
+image_multi_1, image_multi_2 = [...] # prepare additional images
 
-#### Metrics
+prompt_multi = "What is the difference between the following images?\n<image_placeholder><image_placeholder>\nAnswer in German."
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+messages_multi = [
+    {"role": "user", "content": prompt_multi}
+]
 
-[More Information Needed]
+text_multi = processor.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
 
-### Results
+model_inputs = processor(text=[text, text_multi], images=[image, image_multi_1, image_multi_2] return_tensors="pt").to(model.device)
 
-[More Information Needed]
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=128
+)
 
-#### Summary
+[...]
 
+```
 
+## Bias, Risks, and Limitations
 
-## 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
+- General biases, risks, and limitations of large vision-language models like hallucinations or biases from training data apply.
+- This is a research project and *not* recommended for production use.
+- Multilingual: Performance and generation quality can differ widely between languages. 
+- OCR: Model struggles both with small text and writing in non-Latin scripts.
 
-[More Information Needed]
 
-## Citation [optional]
+## Citation
 
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
 **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]
+```
+@article{centurio2025,
+  title={TODO},
+  author={TODO},
+  year={2024},
+  journal={arXiv preprint arXiv:TODO},
+  url={TODO}
+}
+```