Summarization
Transformers
PyTorch
English
llama
text-generation
Meeting
Summarization
text-generation-inference
Instructions to use MeetPEFT/MeetPEFT-7B-16K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MeetPEFT/MeetPEFT-7B-16K with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="MeetPEFT/MeetPEFT-7B-16K")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MeetPEFT/MeetPEFT-7B-16K") model = AutoModelForCausalLM.from_pretrained("MeetPEFT/MeetPEFT-7B-16K", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "merged/only-mb-16k", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "max_position_embeddings": 2048, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "pad_token_id": 0, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.34.0", | |
| "use_cache": true, | |
| "vocab_size": 32001 | |
| } | |