Update README.md

README.md

@@ -49,32 +49,32 @@ The quality of the samples can vary depending on the speaker.
 This may be due to the sensitivity of the model in learning specific frequencies and also due to the samples used for each speaker.
 
 ## How to use
-```python
-import torch
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
-
-input_text = "Sovint em trobo pensant en tot allò que"
-
-model_id  = "projecte-aina/FLOR-6.3B"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-generator = pipeline(
-    "text-generation",
-    model=model_id,
-    tokenizer=tokenizer,
-    torch_dtype=torch.bfloat16,
-    trust_remote_code=True,
-    device_map="auto",
-)
-generation = generator(
-    input_text,
-    do_sample=True,
-    top_k=10,
-    eos_token_id=tokenizer.eos_token_id,
-)
-
-print(f"Result: {generation[0]['generated_text']}")
+
+### Installation
+
+```bash
+pip install git+https://github.com/langtech-bsc/vocos.git@matcha
+```
+You need to install the Catalan phonemizer version of espeak-ng:
+
+```bash
+git clone https://github.com/projecte-aina/espeak-ng.git
+
+export PYTHON=/path/to/env/<env_name>/bin/python
+cd /path/to/espeak-ng
+./autogen.sh
+./configure --prefix=/path/to/espeak-ng
+make
+make install
+
+pip cache purge
+pip install mecab-python3
+pip install unidic-lite
+
 ```
 
+### Generate 
+
 ## Training
 
 ### Adaptation