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Sourabh2/Chemical_compund
Chemical_compund is a machine learning model from Sourabh2. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
4
27% of all-time downloads
All-time downloads
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.safetensors328 MB · 100%
From the Hugging Face model README
To use the model:
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Sourabh2/Chemical_compund", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Sourabh2/Chemical_compund", trust_remote_code=True)
# Set up the device (GPU if available, otherwise CPU)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = model.to(device)
input_str = "Nobelium".lower()
input_ids = tokenizer.encode(input_str, return_tensors='pt').to(device)
output = model.generate(
input_ids,
max_length=200,
num_return_sequences=1,
do_sample=True,
top_k=8,
top_p=0.95,
temperature=0.1,
repetition_penalty=1.2
)
decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
print(decoded_output)