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--- |
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library_name: mlx |
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language: |
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- ar |
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- de |
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- en |
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- es |
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- fr |
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- hi |
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- id |
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- it |
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- pt |
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- th |
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- tl |
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- vi |
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base_model: meta-llama/Llama-4-Scout-17B-16E-Instruct |
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tags: |
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- facebook |
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- meta |
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- pytorch |
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- llama |
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- llama-4 |
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- mlx |
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extra_gated_prompt: '**LLAMA 4 COMMUNITY LICENSE AGREEMENT** |
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Llama 4 Version Effective Date: April 5, 2025 |
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By clicking "I Accept" below or by using or distributing any portion or element |
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extra_gated_fields: |
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First Name: text |
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Last Name: text |
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Date of birth: date_picker |
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Country: country |
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Affiliation: text |
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Job title: |
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type: select |
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options: |
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- Student |
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- Research Graduate |
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- AI researcher |
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- AI developer/engineer |
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- Reporter |
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- Other |
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geo: ip_location |
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? By clicking Submit below I accept the terms of the license and acknowledge that |
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the information I provide will be collected stored processed and shared in accordance |
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extra_gated_description: The information you provide will be collected, stored, processed |
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and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/). |
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edit this form after submission, so please ensure all information is accurate. |
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license: other |
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license_name: llama4 |
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pipeline_tag: text-generation |
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--- |
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# lmstudio-community/meta-llama-Llama-4-Scout-17B-16E-MLX-text-4bit |
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This model [lmstudio-community/meta-llama-Llama-4-Scout-17B-16E-MLX-text-4bit](https://huggingface.co/lmstudio-community/meta-llama-Llama-4-Scout-17B-16E-MLX-text-4bit) was |
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converted to MLX format from [meta-llama/Llama-4-Scout-17B-16E-Instruct](https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct) |
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using mlx-lm version **0.22.4**. |
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## Use with mlx |
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```bash |
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pip install mlx-lm |
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``` |
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```python |
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from mlx_lm import load, generate |
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model, tokenizer = load("lmstudio-community/meta-llama-Llama-4-Scout-17B-16E-MLX-text-4bit") |
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prompt = "hello" |
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if tokenizer.chat_template is not None: |
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messages = [{"role": "user", "content": prompt}] |
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prompt = tokenizer.apply_chat_template( |
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messages, add_generation_prompt=True |
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) |
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response = generate(model, tokenizer, prompt=prompt, verbose=True) |
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``` |
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