Instructions to use bn22/experimental-te-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bn22/experimental-te-ft with Transformers:
# Load model directly from transformers import AutoTokenizer, CLIPTextModelWithProjection tokenizer = AutoTokenizer.from_pretrained("bn22/experimental-te-ft") model = CLIPTextModelWithProjection.from_pretrained("bn22/experimental-te-ft") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +5 -4
- model.safetensors +2 -2
config.json
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{
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"architectures": [
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"
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"attention_dropout": 0.0,
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"bos_token_id": 49406,
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"model_type": "clip_text_model",
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"num_attention_heads": 8,
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"num_hidden_layers": 12,
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"pad_token_id":
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"projection_dim":
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"transformers_version": "5.
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"vocab_size": 49408
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}
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{
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"architectures": [
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"CLIPTextModelWithProjection"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 49406,
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"model_type": "clip_text_model",
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"num_attention_heads": 8,
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"num_hidden_layers": 12,
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"pad_token_id": 49407,
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"projection_dim": 384,
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"transformers_version": "5.10.2",
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"use_cache": false,
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"vocab_size": 49408
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:24681603f6c9cff843ba5ba83c948c9eb3e01707d03605ef4a19b1d6d0db4035
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size 173343824
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