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 model.safetensors from AnkitAI/TinyJev-4B: direct link, hf CLI and curl.
- Browser
- Download file 8.04 GB
-
https://huggingface.co/AnkitAI/TinyJev-4B/resolve/main/model.safetensors
- Command line
-
hf download hf://AnkitAI/TinyJev-4B/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/AnkitAI/TinyJev-4B/resolve/main/model.safetensors
8.04 GB
- Xet hash:
- 5a22a152c538702559928604bf606e0c3b73822941415aad64489b7d3c8e64be
- Size of remote file:
- 8.04 GB
- SHA256:
- 16e69e0c85d698a13a38ac12cefe2139b3ceca45de838a46334278ff34babfa1
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