Text Classification
Transformers
Safetensors
MLX
English
qwen3
feature-extraction
tinyjev
jev
decision-model
system-one
typed-decisions
text-embeddings-inference
Instructions to use AnkitAI/TinyJev-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/TinyJev-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/TinyJev-0.6B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnkitAI/TinyJev-0.6B") model = AutoModel.from_pretrained("AnkitAI/TinyJev-0.6B", device_map="auto") - MLX
How to use AnkitAI/TinyJev-0.6B with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download AnkitAI/TinyJev-0.6B --local-dir TinyJev-0.6B
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,130 Bytes
ed1ee89 c559c2f ed1ee89 c559c2f ed1ee89 | 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 | {
"format": "tinyjev-v2",
"family": "kev",
"name": "TinyJev-0.6B",
"head": {
"head_dim": 256,
"temperature": 1.4640856959456252,
"option_isolation": false,
"temperature_note": "fitted on decision-v7 calibration partition by Kev trial scorer (micro NLL); served probabilities are logits / T"
},
"tokenizer": {
"eos_token_id": 151643,
"pad_token_id": 151643
},
"max_state": 8192,
"max_branch": 8192,
"dtypes": {
"backbone": "float16",
"head": "float32"
},
"upstream": {
"repo": "AnkitAI/TinyJev-0.6B (E1(b): LoRA r16 lr5e-5 seed 2 on Qwen3-0.6B-Base, merged)",
"base_model": "Qwen/Qwen3-0.6B-Base",
"base_revision": "da87bfb608c14b7cf20ba1ce41287e8de496c0cd",
"lora_rank": 16,
"lora_alpha": 32,
"merged_tensors": 196,
"full_finetune": false,
"trained_by": "tinyjev E1(b)",
"trial": "tinyjev-e1-lora/01-trial-1",
"data": "jaredpalmer/kev-suites decision-v7 train",
"transfer_v4_dev_raw": 0.625,
"transfer_v4_dev_calibrated_ece": 0.0739,
"transfer_v4_test_locked_once": 0.6631,
"decision_v7_test_locked_once": 0.8075
}
} |