Instructions to use BAAI/AquilaChat-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/AquilaChat-7B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BAAI/AquilaChat-7B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from BAAI/AquilaChat-7B: direct link, hf CLI and curl.
- Browser
- Download file 503 Bytes
-
https://huggingface.co/BAAI/AquilaChat-7B/resolve/15e92fcbbad90e73c4275bd6aded6f364fd0b934/config.json
- Command line
-
hf download hf://BAAI/AquilaChat-7B@15e92fcbbad90e73c4275bd6aded6f364fd0b934/config.json
-
curl -L -o config.json https://huggingface.co/BAAI/AquilaChat-7B/resolve/15e92fcbbad90e73c4275bd6aded6f364fd0b934/config.json
503 Bytes
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "max_position_embeddings": 2048, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-05, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.28.1", | |
| "use_cache": true, | |
| "vocab_size": 100008 | |
| } | |