Text Generation
PEFT
Safetensors
English
code
cobol
code-generation
mainframe-modernization
lora
sft
trl
unsloth
ministral
conversational
Eval Results (legacy)
Instructions to use axeltta/mistral-axel-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use axeltta/mistral-axel-1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/ministral-3-8b-instruct-2512-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "axeltta/mistral-axel-1") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
| { | |
| "image_break_token": "[IMG_BREAK]", | |
| "image_end_token": "[IMG_END]", | |
| "image_processor": { | |
| "data_format": "channels_first", | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "PixtralImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "patch_size": 14, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 1540 | |
| } | |
| }, | |
| "image_token": "[IMG]", | |
| "patch_size": 14, | |
| "processor_class": "PixtralProcessor", | |
| "spatial_merge_size": 2 | |
| } | |