Instructions to use HHazard/mixtral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HHazard/mixtral with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B-v0.1") model = PeftModel.from_pretrained(base_model, "HHazard/mixtral") - Notebooks
- Google Colab
- Kaggle
Download config.json from HHazard/mixtral: direct link, hf CLI and curl.
- Browser
- Download file 764 Bytes
-
https://huggingface.co/HHazard/mixtral/resolve/main/config.json
- Command line
-
hf download hf://HHazard/mixtral/config.json
-
curl -L -o config.json https://huggingface.co/HHazard/mixtral/resolve/main/config.json
764 Bytes
| { | |
| "_name_or_path": "mistralai/Mixtral-8x7B-v0.1", | |
| "architectures": [ | |
| "MixtralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 32768, | |
| "model_type": "mixtral", | |
| "num_attention_heads": 32, | |
| "num_experts_per_tok": 2, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "num_local_experts": 8, | |
| "output_router_logits": false, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 1000000.0, | |
| "router_aux_loss_coef": 0.02, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.36.1", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |