These are the GGUF files for
QuantaSparkLabs/Quantum-X.
I provide GGUFs and quantizations of publicly available models that do not have a GGUF equivalent available yet,
usually for models I deem interesting and wish to try out.
If there are some quants missing that you'd like me to add, you may request one in the community tab.
If you want to request a public model to be converted, you can also request that in the community tab.
If you have questions regarding this model, please refer to
the original model repo.
You can find more info about me and what I do
here.
1from transformers import AutoTokenizer, AutoModelForCausalLM
2import torch
3
4model_id = "QuantaSparkLabs/Quantum-X"
5tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
6model = AutoModelForCausalLM.from_pretrained(
7 model_id,
8 torch_dtype=torch.float16,
9 device_map="auto",
10 trust_remote_code=True
11)
12
13messages = [
14 {"role": "system", "content": "You are Quantum-X, created by QuantaSparkLabs."},
15 {"role": "user", "content": "What is the capital of France?"}
16]
17inputs = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
18input_ids = tokenizer(inputs, return_tensors="pt").to(model.device)
19
20outputs = model.generate(**input_ids, max_new_tokens=100, temperature=0.7, do_sample=True)
21print(tokenizer.decode(outputs[0], skip_special_tokens=True))
