Update README.md

README.md

@@ -476,19 +476,19 @@ Find below some example scripts on how to use the model:
 
 ## Using the Pytorch model with `transformers`
 
-### Running the model on a CPU or GPU
+### Running the model on a GPU
 
 <details>
 <summary> Click to expand </summary>
 
 First, install the Python packages that are required:
 
-`pip install transformers accelerate sentencepiece`
+`pip install transformers accelerate sentencepiece bitsandbytes`
 
 ```python
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 
-model_name = 'jbochi/madlad400-3b-mt'
+model_name = 'ikeno-ada/madlad400-3b-mt-bitsandbytes-4bit'
 model = T5ForConditionalGeneration.from_pretrained(model_name, device_map="auto")
 tokenizer = T5Tokenizer.from_pretrained(model_name)
 
@@ -502,33 +502,6 @@ tokenizer.decode(outputs[0], skip_special_tokens=True)
 
 </details>
 
-## Running the model with Candle
-
-<details>
-<summary> Click to expand </summary>
-
-Usage with [candle](https://github.com/huggingface/candle):
-
-```bash
-$ cargo run --example t5 --release  -- \
-  --model-id "jbochi/madlad400-3b-mt" \
-  --prompt "<2de> How are you, my friend?" \
-  --decode --temperature 0
-```
-
-We also provide a quantized model (1.65 GB vs the original 11.8 GB file):
-
-```
-cargo run --example quantized-t5 --release  -- \
-  --model-id "jbochi/madlad400-3b-mt" --weight-file "model-q4k.gguf" \
-  --prompt "<2de> How are you, my friend?" \
-  --temperature 0
-...
- Wie geht es dir, mein Freund?
-```
-
-</details>
-
 
 # Uses