base_model, library_name, pipeline_tag, tags
| base_model | library_name | pipeline_tag | tags | ||||
|---|---|---|---|---|---|---|---|
| mistralai/Mistral-7B-Instruct-v0.2 | transformers | text-generation |
|
mistral-7b-detell
MCQuilibrium de-tell model. A QLoRA fine-tune of Mistral-7B-Instruct-v0.2 that rewrites the answer choices of a multiple-choice question to remove tells, the surface artifacts that leak the correct answer. The LoRA adapter has been merged into the base weights, so this repo loads directly.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("ArHFcloud/mistral-7b-detell")
model = AutoModelForCausalLM.from_pretrained("ArHFcloud/mistral-7b-detell", device_map="auto")
messages = [{"role": "user", "content": "...question and choices..."}]
inputs = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
out = model.generate(inputs, max_new_tokens=512)
print(tok.decode(out[0][inputs.shape[-1]:], skip_special_tokens=True))