Instructions to use AbstractFramework/kev-4b-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AbstractFramework/kev-4b-mlx-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download AbstractFramework/kev-4b-mlx-4bit --local-dir kev-4b-mlx-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,552 Bytes
a74b83d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | {
"format": "abstractcore-decision/1",
"kind": "kev",
"head_dim": 256,
"hidden_size": 2560,
"temperature": 2.406050072164233,
"head_file": "head.safetensors",
"runtime": "mlx",
"base": "Qwen/Qwen3.5-4B-Base",
"base_revision": "1001bb4d826a52d1f399e183466143f4da7b741b",
"lora_rank": 16,
"backbone": "merged",
"delimiters": [
"<|fim_prefix|>",
"<|fim_middle|>",
"<|box_start|>",
"<|box_end|>",
"<|fim_suffix|>"
],
"question_types": [
"choice",
"noul",
"score"
],
"max_state_tokens": 65536,
"max_row_tokens": 73728,
"source": {
"adapter_dir": "/Users/albou/.cache/huggingface/hub/models--jaredpalmer--kev-4b/snapshots/6cfce5c2fa4b4bd64026336ab649c5ca78857d52",
"base_dir": "/Users/albou/.cache/huggingface/hub/models--Qwen--Qwen3.5-4B-Base/snapshots/1001bb4d826a52d1f399e183466143f4da7b741b",
"adapter_sha256": "90e817356246e7f18bfa7ca3d31794cd4fbeb3332a66a84cb51d9ceae925f2b2",
"head_sha256": "dd633435998ecc751ac538717a3742e32149500fabf7d7276287dbf0693f347c",
"repos": {
"jaredpalmer/kev-4b": "6cfce5c2fa4b4bd64026336ab649c5ca78857d52",
"Qwen/Qwen3.5-4B-Base": "1001bb4d826a52d1f399e183466143f4da7b741b"
}
},
"license": "apache-2.0",
"quantization_recipe": {
"bits": 4,
"group_size": 32,
"upgrade": {
"linear_attn.in_proj_qkv": 8,
"linear_attn.in_proj_z": 8,
"linear_attn.in_proj_a": 8,
"linear_attn.in_proj_b": 8,
"linear_attn.out_proj": 8
}
},
"merged_tensors": 248,
"tensor_count": 924
} |