Instructions to use ydshieh/tiny-random-GPT2ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-GPT2ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ydshieh/tiny-random-GPT2ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-GPT2ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("ydshieh/tiny-random-GPT2ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Update tiny models for GPT2ForTokenClassification
#1
by ydshieh HF Staff - opened
- config.json +2 -2
- pytorch_model.bin +1 -1
config.json
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@@ -4,9 +4,9 @@
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"GPT2ForTokenClassification"
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],
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"attn_pdrop": 0.1,
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-
"bos_token_id":
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"embd_pdrop": 0.1,
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"eos_token_id":
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"gradient_checkpointing": false,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"GPT2ForTokenClassification"
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],
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"attn_pdrop": 0.1,
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+
"bos_token_id": 0,
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"embd_pdrop": 0.1,
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"eos_token_id": 0,
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"gradient_checkpointing": false,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1665793
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version https://git-lfs.github.com/spec/v1
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oid sha256:675af21044c587d6008bc5b4227115bc584f535a04ff14b2cd3e609ddc0e7e5b
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size 1665793
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