| license: apache-2.0 | |
| pipeline_tag: text-generation | |
| language: | |
| - en | |
| - he | |
| tags: | |
| - pretrained | |
| - mlx | |
| - mlx-my-repo | |
| inference: | |
| parameters: | |
| temperature: 0.6 | |
| base_model: dicta-il/DictaLM-3.0-1.7B-Instruct | |
| # ssdataanalysis/DictaLM-3.0-1.7B-Instruct-mlx-8Bit | |
| The Model [ssdataanalysis/DictaLM-3.0-1.7B-Instruct-mlx-8Bit](https://huggingface.co/ssdataanalysis/DictaLM-3.0-1.7B-Instruct-mlx-8Bit) was converted to MLX format from [dicta-il/DictaLM-3.0-1.7B-Instruct](https://huggingface.co/dicta-il/DictaLM-3.0-1.7B-Instruct) using mlx-lm version **0.29.1**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("ssdataanalysis/DictaLM-3.0-1.7B-Instruct-mlx-8Bit") | |
| 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) | |
| ``` | |