update pipelines and readme

.gitignore

@@ -1,2 +1 @@
 __pycache__/
-best-38.ckpt

README.md

@@ -11,4 +11,31 @@ base_model:
 ---
 
 # Model
-This is a model fine-tuned using PyTorch Lightning...
+This is a sample finetuned model produced under [LLMPot research project](https://github.com/momalab/LLMPot) and explained further in the [related research manuscript](https://arxiv.org/abs/2405.05999).
+
+## How to Use
+
+This model is a fine-tuned version of [`google/byt5-small`](https://huggingface.co/google/byt5-small) for Modbus protocol emulation.
+
+Make sure you have `transformers` and `torch` installed:
+
+```bash
+pip install transformers torch
+```
+
+Load the model and run a single inference.
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("cv43/llmpot")
+model = AutoModelForSeq2SeqLM.from_pretrained("cv43/llmpot")
+
+pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer, framework="pt")
+
+request = "02b10000000b00100000000204ffffffff"
+result = pipe(request)
+print(f"Request: {request}, Response: {result[0]['generated_text']}")
+```
+
+Otherwise you may use our Huggingface Spaces where the model is running on this platform.

pipeline.py

@@ -1,4 +1,10 @@
-from transformers import pipeline
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
-pipe = pipeline("text2text-generation", model="cv43/mbtcp-c0-f1_5_15_3_6_16-a0_39")
-pipe("02b10000000b00100000000204ffffffff")
+tokenizer = AutoTokenizer.from_pretrained("cv43/llmpot")
+model = AutoModelForSeq2SeqLM.from_pretrained("cv43/llmpot")
+
+pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer, framework="pt")
+
+request = "02b10000000b00100000000204ffffffff"
+result = pipe(request)
+print(f"Request: {request}, Response: {result[0]['generated_text']}")