Instructions to use KaiNylund/xglm-564M-lm-wmt-2020-0-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KaiNylund/xglm-564M-lm-wmt-2020-0-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KaiNylund/xglm-564M-lm-wmt-2020-0-en")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KaiNylund/xglm-564M-lm-wmt-2020-0-en") model = AutoModel.from_pretrained("KaiNylund/xglm-564M-lm-wmt-2020-0-en") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +27 -0
- pytorch_model.bin +3 -0
config.json
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{
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"_name_or_path": "./xglm-564M_models/en/2020_0_bytes",
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"activation_dropout": 0,
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"activation_function": "gelu",
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"architectures": [
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"XGLMModel"
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],
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"attention_dropout": 0.1,
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"attention_heads": 16,
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"bos_token_id": 0,
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"d_model": 1024,
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"decoder_start_token_id": 2,
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"dropout": 0.1,
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"eos_token_id": 2,
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"ffn_dim": 4096,
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"init_std": 0.02,
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"layerdrop": 0.0,
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"max_position_embeddings": 2048,
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"model_type": "xglm",
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"num_layers": 24,
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"pad_token_id": 1,
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"scale_embedding": true,
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"torch_dtype": "float32",
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"transformers_version": "4.18.0",
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"use_cache": true,
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"vocab_size": 256008
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:42e94637f6080af25263900f3bc14245bf47e839188b1253f69a0cbd21752e2b
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size 2266371869
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