| --- |
| base_model: darkc0de/XortronCriminalComputingConfig |
| library_name: transformers |
| tags: |
| - mlx |
| license: apache-2.0 |
| language: |
| - en |
| pipeline_tag: text-generation |
| --- |
| |
| # Xonaz81/XortronCriminalComputingConfig-mlx-6Bit |
|
|
| Because this model seems to be promising and there was no 6-bit version to be found, I decided to create one from the full model weights. This is a normal 6-bit MLX quant. No advanced DWQ quants for now but coming in the future! The original model [Xonaz81/XortronCriminalComputingConfig-mlx-6Bit](https://huggingface.co/Xonaz81/XortronCriminalComputingConfig-mlx-6Bit) was converted to MLX format from [darkc0de/XortronCriminalComputingConfig](https://huggingface.co/darkc0de/XortronCriminalComputingConfig) using mlx-lm |
|
|
| ## Use with mlx or LM-studio |
|
|
| ```bash |
| pip install mlx-lm |
| ``` |
|
|
| ```python |
| from mlx_lm import load, generate |
| |
| model, tokenizer = load("Xonaz81/XortronCriminalComputingConfig-mlx-6Bit") |
| |
| prompt="hello" |
| |
| if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: |
| messages = [{"role": "user", "content": prompt}] |
| prompt = tokenizer.apply_chat_template( |
| messages, tokenize=False, add_generation_prompt=True |
| ) |
| |
| response = generate(model, tokenizer, prompt=prompt, verbose=True) |
| ``` |
