Instructions to use FTK11558/RepBend_Mistral_7B-APS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FTK11558/RepBend_Mistral_7B-APS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="FTK11558/RepBend_Mistral_7B-APS", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("FTK11558/RepBend_Mistral_7B-APS", trust_remote_code=True) model = AutoModel.from_pretrained("FTK11558/RepBend_Mistral_7B-APS", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "FTK11558/RepBend_Mistral_7B-APS", | |
| "model_type": "HookedMistralForCausalLM", | |
| "architectures": [ | |
| "HookedMistralForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoModel": "HookedMistralForCausalLM.HookedMistralForCausalLM", | |
| "AutoModelForCausalLM": "HookedMistralForCausalLM.HookedMistralForCausalLM" | |
| }, | |
| "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": "mistral", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 1000000.0, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.40.0", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |