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
File size: 842 Bytes
29c6fb1 | 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 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": null,
"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"errors": "replace",
"extra_special_tokens": {
"extra_0": "<|im_start|>",
"extra_1": "<|im_end|>",
"extra_2": "<|object_ref_start|>",
"extra_3": "<|object_ref_end|>",
"extra_4": "<|box_start|>",
"extra_5": "<|box_end|>",
"extra_6": "<|quad_start|>",
"extra_7": "<|quad_end|>",
"extra_8": "<|vision_start|>",
"extra_9": "<|vision_end|>",
"extra_10": "<|vision_pad|>",
"extra_11": "<|image_pad|>",
"extra_12": "<|video_pad|>"
},
"is_local": false,
"local_files_only": false,
"model_max_length": 131072,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
} |