Instructions to use iisys-hof/OLaPhLLM_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iisys-hof/OLaPhLLM_v2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="iisys-hof/OLaPhLLM_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("iisys-hof/OLaPhLLM_v2") model = AutoModelForCausalLM.from_pretrained("iisys-hof/OLaPhLLM_v2") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -67,8 +67,8 @@ prompt = f"Translate this from {lang} to Phones:\n{lang}: "
|
|
| 67 |
|
| 68 |
inputs = tokenizer(f"{prompt}{sentence}\nPhones:", return_tensors="pt").to("cuda")
|
| 69 |
|
| 70 |
-
outputs = model.generate(**inputs, max_new_tokens=256
|
| 71 |
-
phonemized = tokenizer.decode(outputs[0], skip_special_tokens=
|
| 72 |
phonemized = phonemized.split("\n")[-1].replace("Phones:", "")
|
| 73 |
|
| 74 |
print(phonemized)
|
|
|
|
| 67 |
|
| 68 |
inputs = tokenizer(f"{prompt}{sentence}\nPhones:", return_tensors="pt").to("cuda")
|
| 69 |
|
| 70 |
+
outputs = model.generate(**inputs, max_new_tokens=256)
|
| 71 |
+
phonemized = tokenizer.decode(outputs[0], skip_special_tokens=True)
|
| 72 |
phonemized = phonemized.split("\n")[-1].replace("Phones:", "")
|
| 73 |
|
| 74 |
print(phonemized)
|