Instructions to use klcsp/mistral7b-lora-coding-11-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use klcsp/mistral7b-lora-coding-11-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.3") model = PeftModel.from_pretrained(base_model, "klcsp/mistral7b-lora-coding-11-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_attn_implementation_autoset": true, | |
| "_name_or_path": "mistralai/Mistral-7B-v0.3", | |
| "architectures": [ | |
| "MistralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 32768, | |
| "eos_token_id": 32769, | |
| "head_dim": 128, | |
| "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, | |
| "pad_token_id": 32769, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 1000000.0, | |
| "sliding_window": null, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.46.2", | |
| "use_cache": true, | |
| "vocab_size": 32770 | |
| } | |