Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
Generated from Trainer
dataset_size:124788
loss:CachedGISTEmbedLoss
Instructions to use pj-mathematician/JobGTE-7b-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pj-mathematician/JobGTE-7b-Lora with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pj-mathematician/JobGTE-7b-Lora") sentences = [ "其他机械、设备和有形货物租赁服务代表", "其他机械和设备租赁服务工作人员", "电子和电信设备及零部件物流经理", "工业主厨" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "Alibaba-NLP/gte-Qwen2-7B-instruct", | |
| "bias": "none", | |
| "eva_config": null, | |
| "exclude_modules": null, | |
| "fan_in_fan_out": false, | |
| "inference_mode": false, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 64, | |
| "lora_bias": false, | |
| "lora_dropout": 0.1, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 32, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "o_proj" | |
| ], | |
| "task_type": "FEATURE_EXTRACTION", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |