Instructions to use apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7") - Notebooks
- Google Colab
- Kaggle
Download config.json from apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7: direct link, hf CLI and curl.
- Browser
- Download file 658 Bytes
-
https://huggingface.co/apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7/resolve/f6dc3cb80bd41995ebda5c6559ec1298769981b4/config.json
- Command line
-
hf download hf://apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7@f6dc3cb80bd41995ebda5c6559ec1298769981b4/config.json
-
curl -L -o config.json https://huggingface.co/apriasmoro/5401ffa9-6e3d-478c-aac2-e3aff6d7efc7/resolve/f6dc3cb80bd41995ebda5c6559ec1298769981b4/config.json
658 Bytes
| { | |
| "_attn_implementation_autoset": true, | |
| "architectures": [ | |
| "MistralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 32000, | |
| "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, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.51.3", | |
| "use_cache": false, | |
| "vocab_size": 32002 | |
| } | |