Feature Extraction
MLX
Safetensors
qwen2
embeddings
sentence-similarity
quantization
omlx
q6
6-bit
custom_code
Instructions to use TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir gte-Qwen2-1.5B-instruct-MLX-Q6 TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 1,917 Bytes
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"schema_version": 1,
"published_repository": "TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-Q6",
"family": "gte-Qwen2-1.5B-instruct",
"variant": "Q6",
"upstream_repository": "Alibaba-NLP/gte-Qwen2-1.5B-instruct",
"upstream_revision": "a9af15a6372d7d6b25e9fb07c2ccb9e1fe645644",
"upstream_revision_evidence": "upstream revision verified at publication time; historical local snapshot metadata was not retained",
"direct_parent": "TiGa-RCE/gte-Qwen2-1.5B-instruct-MLX-BF16",
"direct_parent_weight_hashes": [
{
"file": "model.safetensors",
"sha256": "9e9da58bd1371c47a08bc82f58bd29d33a6831094372dd717d68148f061dd11a",
"bytes": 3552432732
}
],
"conversion": {
"method": "Q uniform affine quantization",
"nominal_bits": 6,
"group_size": 64,
"importance_matrix": false,
"importance_matrix_samples": null,
"importance_matrix_sequence_length": null,
"stack": {
"omlx": "0.5.3",
"mlx_lm": "0.31.3",
"mlx": "0.32.0"
},
"lossy_parent": false
},
"weight_files": [
{
"file": "model.safetensors",
"sha256": "2da02d9f35059fd21ef065dda0c77b7f5fabda4bed096fb83d7607ec519ee7a7",
"bytes": 1443414458
}
],
"evaluation": {
"pair_count": 24,
"top1": 1.0,
"recall_at_5": 1.0,
"mrr": 1.0,
"mean_aligned_embedding_cosine_vs_bf16": 0.9977855682373047,
"minimum_aligned_embedding_cosine_vs_bf16": 0.9961316585540771,
"score_rmse_vs_bf16": 0.004666702821850777,
"queries_with_rank_change": 0,
"gate_passed": true,
"gate_criteria": {
"top1_delta_min": 0.0,
"recall_at_5_delta_min": 0.0,
"mrr_delta_min": -0.01,
"minimum_aligned_embedding_cosine_min": 0.99,
"queries_with_rank_change_max": 2
}
},
"collection": "https://huggingface.co/collections/TiGa-RCE/mlx-embedding-quantization-matrix-q-oq-oqe-at-4-6-8-bit-6a68d11afb238d4fe967d70b"
}
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