How to run inference:
import transformers
import torch
def fmt_prompt(prompt: str) -> str:
return f"""[Instructions]:\n{prompt}\n\n[Response]:"""
if __name__ == "__main__":
model_name = "abacaj/mistral-7b-sft"
tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
model = (
transformers.AutoModelForCausalLM.from_pretrained(
model_name,
)
.to("cuda:0")
.eval()
)
prompt = "If A is greater than B and B is greater than C does that make A greater than C?"
prompt_input = fmt_prompt(prompt)
inputs = tokenizer(prompt_input, return_tensors="pt").to(model.device)
input_ids_cutoff = inputs.input_ids.size(dim=1)
with torch.no_grad():
generated_ids = model.generate(
**inputs,
use_cache=True,
max_new_tokens=512,
temperature=0.2,
top_p=0.95,
do_sample=True,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.pad_token_id,
)
completion = tokenizer.decode(
generated_ids[0][input_ids_cutoff:],
skip_special_tokens=True,
)
print(completion)
Evals:
Code to train model: https://github.com/abacaj/train-with-fsdp
- Downloads last month
- 86
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Evaluation results
- pass@1 on HumanEvalself-reported54.270
- pass@1 on MBPPself-reported38.000
- pass@1 on MMLUself-reported45.890