Update README.md

README.md

@@ -23,11 +23,6 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-small) on the annotated [Dreambank.net](https://dreambank.net/) dataset.It achieves the following results on the evaluation set:
 
-
-## Model description
-
-More information needed
-
 ## Intended uses & limitations
 
 This model is designed for research purposes. See the disclaimer for more details.
@@ -115,6 +110,41 @@ in annotating dream reports for research purposes, as well as detailing their st
 - Datasets 3.0.1
 - Tokenizers 0.19.1
 
+# Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_id = "jrc-ai/PreDA-base"
+device = "cpu"
+encoder_max_length = 100
+decoder_max_length = 50
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+
+dream = "I was talking with my brother about my birthday dinner. I was feeling sad."
+prefixes = ["Emotion", "Activities", "Characters"]
+text_inputs = ["{} : {}".format(p, dream) for p in prefixes]
+
+inputs = tokenizer(
+    text_inputs,
+    max_length=encoder_max_length,
+    truncation=True,
+    padding=True,
+    return_tensors="pt"
+)
+
+output = model.generate(
+    **inputs.to(device),
+    do_sample=False,
+    max_length=decoder_max_length,
+)
+
+for decode_dream in output:
+    print(tokenizer.decode(decode_dream, skip_special_tokens=True))
+```
+
 # Dual-Use Implication
 Upon evaluation we identified no dual-use implication for the present model