Instructions to use hf-internal-testing/tiny-random-BloomForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BloomForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-BloomForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BloomForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-BloomForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "apply_residual_connection_post_layernorm": false, | |
| "architectures": [ | |
| "BloomForSequenceClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "bos_token_id": 1, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "gradient_checkpointing": false, | |
| "hidden_dropout": 0.1, | |
| "hidden_size": 32, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2" | |
| }, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2 | |
| }, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "bloom", | |
| "n_head": 4, | |
| "n_layer": 5, | |
| "n_positions": 512, | |
| "pad_token_id": 3, | |
| "pretraining_tp": 1, | |
| "seq_length": 7, | |
| "slow_but_exact": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.25.0.dev0", | |
| "type_vocab_size": 16, | |
| "use_cache": true, | |
| "vocab_size": 1024 | |
| } | |