Text Classification
Transformers
TensorBoard
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use lomov/targetsandgoalsv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lomov/targetsandgoalsv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lomov/targetsandgoalsv1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lomov/targetsandgoalsv1") model = AutoModelForSequenceClassification.from_pretrained("lomov/targetsandgoalsv1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from lomov/targetsandgoalsv1: direct link, hf CLI and curl.
- Browser
- Download file 1.26 kB
-
https://huggingface.co/lomov/targetsandgoalsv1/resolve/main/config.json
- Command line
-
hf download hf://lomov/targetsandgoalsv1/config.json
-
curl -L -o config.json https://huggingface.co/lomov/targetsandgoalsv1/resolve/main/config.json
1.26 kB
| { | |
| "_name_or_path": "climatebert/distilroberta-base-climate-f", | |
| "_num_labels": 5, | |
| "architectures": [ | |
| "RobertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "NO", | |
| "1": "Plan on how to achieve the targets", | |
| "2": "Progress on achieving climate-related targets", | |
| "3": "Targets as a part of the business model", | |
| "4": "Use of carbon offsets" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "NO": 0, | |
| "Plan on how to achieve the targets": 1, | |
| "Progress on achieving climate-related targets": 2, | |
| "Targets as a part of the business model": 3, | |
| "Use of carbon offsets": 4 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "roberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "problem_type": "single_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.40.1", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 50500 | |
| } | |