Commonsense-QA-Mistral-7B
This is a finetuned model of mistralai/Mistral-7B-Instruct-v0.1 with tau/commonsense_qa dataset.
The model is loaded in 4-bit and fine-tuned with LoRA.
Usage
Loading of model:
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained(
"rvv-karma/Commonsense-QA-Mistral-7B",
low_cpu_mem_usage=True,
return_dict=True,
torch_dtype=torch.bfloat16,
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("rvv-karma/Commonsense-QA-Mistral-7B", trust_remote_code=True)
tokenizer.pad_token = tokenizer.eos_token
tokenizer.padding_side = "left"
Sample:
pipe = pipeline(
task="text-generation",
model=model,
tokenizer=tokenizer,
return_full_text=False,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=13,
max_new_tokens=8
)
prompt = """<s>
QUESTION:
The sensor would just the distance then set off an alarm, the installation expert explained it was called a what kind of sensor?
OPTIONS:
["near", "closeness", "here", "proximity", "this"]
ANSWER:
"""
result = pipe(prompt)
generated = result[0]['generated_text']
print(generated)
# Output: proximity