Instructions to use bumblebee-testing/tiny-random-GPTBigCodeModel-multi_query-False with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-GPTBigCodeModel-multi_query-False with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bumblebee-testing/tiny-random-GPTBigCodeModel-multi_query-False")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bumblebee-testing/tiny-random-GPTBigCodeModel-multi_query-False") model = AutoModel.from_pretrained("bumblebee-testing/tiny-random-GPTBigCodeModel-multi_query-False", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "hf-internal-testing/tiny-random-GPTBigCodeModel", | |
| "activation_function": "relu", | |
| "architectures": [ | |
| "GPTBigCodeModel" | |
| ], | |
| "attention_softmax_in_fp32": false, | |
| "attn_pdrop": 0.1, | |
| "bos_token_id": 0, | |
| "embd_pdrop": 0.1, | |
| "eos_token_id": 0, | |
| "gradient_checkpointing": false, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "gpt_bigcode", | |
| "multi_query": false, | |
| "n_embd": 32, | |
| "n_head": 4, | |
| "n_inner": 37, | |
| "n_layer": 5, | |
| "n_positions": 512, | |
| "pad_token_id": 1021, | |
| "reorder_and_upcast_attn": false, | |
| "resid_pdrop": 0.1, | |
| "scale_attention_softmax_in_fp32": false, | |
| "scale_attn_by_inverse_layer_idx": false, | |
| "scale_attn_weights": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.35.0", | |
| "type_vocab_size": 16, | |
| "use_cache": true, | |
| "vocab_size": 1024 | |
| } | |