Instructions to use ModelSpace/GemmaX2-28-2B-Pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelSpace/GemmaX2-28-2B-Pretrain with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="ModelSpace/GemmaX2-28-2B-Pretrain")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ModelSpace/GemmaX2-28-2B-Pretrain") model = AutoModelForCausalLM.from_pretrained("ModelSpace/GemmaX2-28-2B-Pretrain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 891 Bytes
b846ce5 07292b9 b846ce5 | 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 31 32 33 34 | {
"_name_or_path": "/mnt/pfs/cuimenglong/huggingface/models/Gemma2-2B",
"architectures": [
"Gemma2ForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"attn_logit_softcapping": 50.0,
"bos_token_id": 2,
"cache_implementation": "hybrid",
"eos_token_id": 1,
"final_logit_softcapping": 30.0,
"head_dim": 256,
"hidden_act": "gelu_pytorch_tanh",
"hidden_activation": "gelu_pytorch_tanh",
"hidden_size": 2304,
"initializer_range": 0.02,
"intermediate_size": 9216,
"max_position_embeddings": 8192,
"model_type": "gemma2",
"num_attention_heads": 8,
"num_hidden_layers": 26,
"num_key_value_heads": 4,
"pad_token_id": 0,
"query_pre_attn_scalar": 256,
"rms_norm_eps": 1e-06,
"rope_theta": 10000.0,
"sliding_window": 4096,
"torch_dtype": "bfloat16",
"transformers_version": "4.44.2",
"use_cache": true,
"vocab_size": 256000
}
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