Instructions to use Muennighoff/SGPT-125M-mean-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Muennighoff/SGPT-125M-mean-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Muennighoff/SGPT-125M-mean-nli") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use Muennighoff/SGPT-125M-mean-nli with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Muennighoff/SGPT-125M-mean-nli") model = AutoModel.from_pretrained("Muennighoff/SGPT-125M-mean-nli") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "EleutherAI/gpt-neo-125M", | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "GPTNeoModel" | |
| ], | |
| "attention_dropout": 0, | |
| "attention_layers": [ | |
| "global", | |
| "local", | |
| "global", | |
| "local", | |
| "global", | |
| "local", | |
| "global", | |
| "local", | |
| "global", | |
| "local", | |
| "global", | |
| "local" | |
| ], | |
| "attention_types": [ | |
| [ | |
| [ | |
| "global", | |
| "local" | |
| ], | |
| 6 | |
| ] | |
| ], | |
| "bos_token_id": 50256, | |
| "embed_dropout": 0, | |
| "eos_token_id": 50256, | |
| "gradient_checkpointing": false, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": null, | |
| "layer_norm_epsilon": 1e-05, | |
| "max_position_embeddings": 2048, | |
| "model_type": "gpt_neo", | |
| "num_heads": 12, | |
| "num_layers": 12, | |
| "resid_dropout": 0, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.12.3", | |
| "use_cache": true, | |
| "vocab_size": 50257, | |
| "window_size": 256 | |
| } | |