Instructions to use X-D-Lab/MindChat-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use X-D-Lab/MindChat-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="X-D-Lab/MindChat-7B", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("X-D-Lab/MindChat-7B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "/code/internlm", | |
| "architectures": [ | |
| "InternLMForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_internlm.InternLMConfig", | |
| "AutoModel": "modeling_internlm.InternLMForCausalLM", | |
| "AutoModelForCausalLM": "modeling_internlm.InternLMForCausalLM" | |
| }, | |
| "bias": true, | |
| "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": "internlm", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-06, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.30.0", | |
| "use_cache": true, | |
| "vocab_size": 103168 | |
| } | |