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-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/TinyJev-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/TinyJev-4B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("AnkitAI/TinyJev-4B") model = AutoModel.from_pretrained("AnkitAI/TinyJev-4B", device_map="auto") - MLX
How to use AnkitAI/TinyJev-4B with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir TinyJev-4B AnkitAI/TinyJev-4B
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download head.safetensors from AnkitAI/TinyJev-4B: direct link, hf CLI and curl.
- Browser
- Download file 5.25 MB
-
https://huggingface.co/AnkitAI/TinyJev-4B/resolve/main/head.safetensors
- Command line
-
hf download hf://AnkitAI/TinyJev-4B/head.safetensors
-
curl -L -o head.safetensors https://huggingface.co/AnkitAI/TinyJev-4B/resolve/main/head.safetensors
5.25 MB
- Xet hash:
- 5f3ff58c44ebdbeb258afd6bc6058ac803465aacaf1bbab644bf9c20635857ad
- Size of remote file:
- 5.25 MB
- SHA256:
- ca7d3b4d3b5bd9bbd65cb5372233971c49e5c1c7531053cefda3ec5a7ffa1b40
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