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!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "birgermoell/Rapid-Cycling"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Runs of birgermoell Rapid-Cycling on huggingface.co
23
Total runs
2
24-hour runs
4
3-day runs
3
7-day runs
2
30-day runs
More Information About Rapid-Cycling huggingface.co Model
Rapid-Cycling huggingface.co
Rapid-Cycling huggingface.co is an AI model on huggingface.co that provides Rapid-Cycling's model effect (), which can be used instantly with this birgermoell Rapid-Cycling model. huggingface.co supports a free trial of the Rapid-Cycling model, and also provides paid use of the Rapid-Cycling. Support call Rapid-Cycling model through api, including Node.js, Python, http.
Rapid-Cycling huggingface.co is an online trial and call api platform, which integrates Rapid-Cycling's modeling effects, including api services, and provides a free online trial of Rapid-Cycling, you can try Rapid-Cycling online for free by clicking the link below.
birgermoell Rapid-Cycling online free url in huggingface.co:
Rapid-Cycling is an open source model from GitHub that offers a free installation service, and any user can find Rapid-Cycling on GitHub to install. At the same time, huggingface.co provides the effect of Rapid-Cycling install, users can directly use Rapid-Cycling installed effect in huggingface.co for debugging and trial. It also supports api for free installation.