Saved file metadata (12 files)
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model-00001-of-00002.safetensors
d72d94e911b046e7a0cafbdc288877936194964b4990da9378f80e86e2813f8e
model-00002-of-00002.safetensors
f71d5c81e5bd67097b2b01c2da82339a97feddf73b88391fb524e7a8b7404f00
tokenizer.json
9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
vocab.json
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merges.txt
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model.safetensors.index.json
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tokenizer_config.json
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.gitattributes
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README.md
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config.json
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special_tokens_map.json
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added_tokens.json
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Saved model card (historical)
mlx-community/Qwen2.5-Coder-14B-Instruct-abliterated-4bit
The Model mlx-community/Qwen2.5-Coder-14B-Instruct-abliterated-4bit was converted to MLX format from huihui-ai/Qwen2.5-Coder-14B-Instruct-abliterated using mlx-lm version 0.20.5.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Qwen2.5-Coder-14B-Instruct-abliterated-4bit")
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)
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