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
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tinyjev-0.6b: standard layout, fp16 backbone, fp32 head, fitted temperature
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