Instructions to use HuggingFaceH4/tiny-random-LlamaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceH4/tiny-random-LlamaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceH4/tiny-random-LlamaForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceH4/tiny-random-LlamaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from HuggingFaceH4/tiny-random-LlamaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 580 Bytes
-
https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/5ce65cd8e9a5893055fac24989b8e3d32cfdb79f/config.json
- Command line
-
hf download hf://HuggingFaceH4/tiny-random-LlamaForSequenceClassification@5ce65cd8e9a5893055fac24989b8e3d32cfdb79f/config.json
-
curl -L -o config.json https://huggingface.co/HuggingFaceH4/tiny-random-LlamaForSequenceClassification/resolve/5ce65cd8e9a5893055fac24989b8e3d32cfdb79f/config.json
580 Bytes
| { | |
| "_name_or_path": "HuggingFaceH4/tiny-random-LlamaForCausalLM", | |
| "architectures": [ | |
| "LlamaForSequenceClassification" | |
| ], | |
| "bos_token_id": 0, | |
| "eos_token_id": 1, | |
| "hidden_act": "silu", | |
| "hidden_size": 16, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 64, | |
| "max_position_embeddings": 2048, | |
| "model_type": "llama", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 2, | |
| "pad_token_id": -1, | |
| "rms_norm_eps": 1e-06, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.28.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |