Text Classification
TensorRT
Core ML
ONNX
Safetensors
OpenVINO
code
multilingual
xlm-roberta
knowledge-graph
relation-extraction
relation-classification
cross-encoder
knowledge-distillation
Instructions to use faxenoff/code-daemon-relation-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use faxenoff/code-daemon-relation-v1 with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download model_gpu_mlx0.32/config.json from faxenoff/code-daemon-relation-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/faxenoff/code-daemon-relation-v1/resolve/main/model_gpu_mlx0.32/config.json
- Command line
-
hf download hf://faxenoff/code-daemon-relation-v1/model_gpu_mlx0.32/config.json
-
curl -L -o config.json https://huggingface.co/faxenoff/code-daemon-relation-v1/resolve/main/model_gpu_mlx0.32/config.json
1.78 kB
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "XLMRobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "custom_head": "entity_start_marker_meanmask (concat E1,E2 -> Linear); [CLS] is not read", | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 384, | |
| "id2label": { | |
| "0": "NO_RELATION", | |
| "1": "semantically_similar_to", | |
| "2": "supersedes_or_conflicts", | |
| "3": "depends_on" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "is_decoder": false, | |
| "label2id": { | |
| "NO_RELATION": 0, | |
| "semantically_similar_to": 1, | |
| "supersedes_or_conflicts": 2, | |
| "depends_on": 3 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "num_labels": 4, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.1.0", | |
| "type_vocab_size": 1, | |
| "ultracode_note": "Inference artefact is model.onnx (inputs: input_ids, attention_mask; output: logits[batch, 4]). Feed the pair as (empty query, marked passage).", | |
| "use_cache": true, | |
| "vocab_size": 250006, | |
| "ultracode": { | |
| "format": "raw-safetensors/1", | |
| "exported_from": "model.onnx", | |
| "onnx_sha256": "9189bfedd376d2a08acd18e7b490000d5f78458c3e4388d1089704319a115840", | |
| "head": "entity_pool", | |
| "position_ids": "roberta", | |
| "pooling": "mean of the last hidden state over the tokens equal to each marker id; concat(E1, E2) -> classifier", | |
| "entity_marker_ids": [ | |
| 250002, | |
| 250004 | |
| ] | |
| } | |
| } | |