Text Classification
Transformers
Safetensors
English
bert
cross-encoder
information-retrieval
job-skill-matching
esco
talentclef
reranking
Eval Results (legacy)
text-embeddings-inference
Instructions to use talentguide/skillscout-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use talentguide/skillscout-reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="talentguide/skillscout-reranker")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("talentguide/skillscout-reranker") model = AutoModelForSequenceClassification.from_pretrained("talentguide/skillscout-reranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from talentguide/skillscout-reranker: direct link, hf CLI and curl.
- Browser
- Download file 1.08 kB
-
https://huggingface.co/talentguide/skillscout-reranker/resolve/main/config.json
- Command line
-
hf download hf://talentguide/skillscout-reranker/config.json
-
curl -L -o config.json https://huggingface.co/talentguide/skillscout-reranker/resolve/main/config.json
1.08 kB
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "is_decoder": false, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "sentence_transformers": { | |
| "activation_fn": "torch.nn.modules.linear.Identity", | |
| "version": "5.3.0" | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.5.0", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |