Instructions to use facebook/blenderbot-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/blenderbot-3B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-3B") model = AutoModelForSeq2SeqLM.from_pretrained("facebook/blenderbot-3B", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from facebook/blenderbot-3B: direct link, hf CLI and curl.
- Browser
- Download file 296 Bytes
-
https://huggingface.co/facebook/blenderbot-3B/resolve/refs%2Fpr%2F10/tokenizer_config.json
- Command line
-
hf download hf://facebook/blenderbot-3B@refs/pr/10/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/facebook/blenderbot-3B/resolve/refs%2Fpr%2F10/tokenizer_config.json
296 Bytes
| {"add_prefix_space": true, "tokenizer_class_name": "BlenderbotTokenizer", "model_max_length": 128, "chat_template": "{% for message in messages %}{% if message['role'] == 'user' %}{{ ' ' }}{% endif %}{{ message['content'] }}{% if not loop.last %}{{ ' ' }}{% endif %}{% endfor %}{{ eos_token }}"} |