Instructions to use nhorlava/tiny-llama-amd-workshop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhorlava/tiny-llama-amd-workshop with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nhorlava/tiny-llama-amd-workshop", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nhorlava/tiny-llama-amd-workshop", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from nhorlava/tiny-llama-amd-workshop: direct link, hf CLI and curl.
- Browser
- Download file 493 Bytes
-
https://huggingface.co/nhorlava/tiny-llama-amd-workshop/resolve/main/config.json
- Command line
-
hf download hf://nhorlava/tiny-llama-amd-workshop/config.json
-
curl -L -o config.json https://huggingface.co/nhorlava/tiny-llama-amd-workshop/resolve/main/config.json
493 Bytes
| { | |
| "architectures": [ | |
| "TinyLlamaV2" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "tiny_llama.TinyLlamaConfig", | |
| "AutoModel": "tiny_llama.TinyLlamaV2" | |
| }, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "hidden_dim": 768, | |
| "intermediate_dim": 3072, | |
| "max_seq_len": 1024, | |
| "model_type": "tiny_llama_v2", | |
| "n_heads": 12, | |
| "n_kv_heads": 4, | |
| "n_layers": 12, | |
| "norm_eps": 1e-06, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.17.0", | |
| "vocab_size": 50257 | |
| } | |