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ope_bert_v1.2
RyotaroOKabe/ope_bert_v1.2
ope_bert_v1.2 is a fill-mask model from RyotaroOKabe. Use it when you need the model to fill a missing word. It is set up for transformers.
random.seed(seedn) sampleratio = 0.5 datapath = '/home/rokabe/data2/cava/data/solid-statedataset2019-06-27upd.json' path to the inorganic crystal synthesis data (json) data = json.load(open(datapath, 'r')) numsample =…
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Dec 8, 2023
- Updated
- Dec 8, 2023
- SHA
- 4cf0fff3
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Model card
From the Hugging Face model README
random.seed(seedn)
sample_ratio = 0.5
data_path = '/home/rokabe/data2/cava/data/solid-state_dataset_2019-06-27_upd.json' # path to the inorganic crystal synthesis data (json)
data = json.load(open(data_path, 'r'))
num_sample = int(len(data)*sample_ratio)
separator=' || '
cut = ';'
rand_indices = random.sample(range(len(data)), num_sample)
data1 = [data[i] for i in rand_indices]
dataset = Dataset_Ceq2Ope(data1, index=None, te_ratio=0.1, separator=separator, cut=cut).dataset
hf_model = "distilbert-base-uncased"
model_name = hf_usn + '/ope_bert_v1.2'# '/syn_distilgpt2_v2'
tk_model = hf_model #"Dagobert42/gpt2-finetuned-material-synthesis"#'m3rg-iitd/matscibert'##hf_model # set tokenizer model loaded from HF (usually same as hf_model)
load_pretrained=False # If True, load the model from 'model_name'. Else, load the pre-trained model from hf_model.
pad_tokenizer=False
save_indices = True
rm_ckpts = True
- Task
- Fill-Mask
- Library
- transformers
- Type
- distilbert
- Created
- Dec 8, 2023
- Updated
- Dec 8, 2023