Instructions to use shareAI/llama2-13b-Chinese-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shareAI/llama2-13b-Chinese-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="shareAI/llama2-13b-Chinese-chat")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shareAI/llama2-13b-Chinese-chat", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "/data/llm/weights/Llama-2-13B-fp16", | |
| "bias": "none", | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "lora_alpha": 16, | |
| "lora_dropout": 0.05, | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 64, | |
| "revision": null, | |
| "target_modules": [ | |
| "gate_proj", | |
| "q_proj", | |
| "up_proj", | |
| "k_proj", | |
| "o_proj", | |
| "v_proj", | |
| "down_proj" | |
| ], | |
| "task_type": "CAUSAL_LM" | |
| } |