Update README.md

README.md

@@ -7,26 +7,35 @@ base_model: monsoon-nlp/tinyllama-mixpretrain-quinoa-sciphi
 model-index:
 - name: tinyllama-mixpretrain-uniprottune
   results: []
+datasets:
+- monsoon-nlp/greenbeing-proteins
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # tinyllama-mixpretrain-uniprottune
 
-This model is a fine-tuned version of [monsoon-nlp/tinyllama-mixpretrain-quinoa-sciphi](https://huggingface.co/monsoon-nlp/tinyllama-mixpretrain-quinoa-sciphi) on the None dataset.
+This is an adapter of the [monsoon-nlp/tinyllama-mixpretrain-quinoa-sciphi](https://huggingface.co/monsoon-nlp/tinyllama-mixpretrain-quinoa-sciphi) 
+model on the GreenBeing dataset finetuning split (minus maize/corn/*Zea*, which I left for evaluation).
+
+## Usage
 
-## Model description
+```
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer
 
-More information needed
+# this model
+model = AutoPeftModelForCausalLM.from_pretrained("monsoon-nlp/tinyllama-mixpretrain-uniprottune").to("cuda")
+# base model for the tokenizer
+tokenizer = AutoTokenizer.from_pretrained("monsoon-nlp/tinyllama-mixpretrain-quinoa-sciphi")
 
-## Intended uses & limitations
+inputs = tokenizer("<sequence> Subcellular locations:", return_tensors="pt")
+outputs = model.generate(input_ids=inputs["input_ids"].to("cuda"), max_new_tokens=50)
+print(tokenizer.batch_decode(outputs, skip_special_tokens=True)[0])
+```
 
-More information needed
+Inference Notebook: https://colab.research.google.com/drive/1UTavcVpqWkp4C_GkkS_HxDQ0Orpw43iu?usp=sharing
 
-## Training and evaluation data
+It seems unreliable on the *Zea* proteins. Getting a lot of the same answers for Subcellular locations.
 
-More information needed
 
 ## Training procedure
 
@@ -42,8 +51,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 10
 - num_epochs: 1
 
-### Training results
-
 
 
 ### Framework versions