INTELLECT-3-REAP-50

72
4
license:apache-2.0
by
0xSero
Language Model
OTHER
New
72 downloads
Early-stage
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Quick Summary

AI model with specialized capabilities.

Code Examples

REAP Configurationyaml
dataset: 0xSero/glm47-reap-calibration-v2
samples: 1360
  - evol-codealpaca-v1: 700 (code generation)
  - xlam-function-calling-60k: 330 (function calling)
  - SWE-smith-trajectories: 330 (agentic multi-turn)
distance_measure: angular
seed: 42
model_max_length: 2048
compression_ratio: 0.50
prune_method: reap
Usagepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained(
    "0xSero/INTELLECT-3-REAP-50",
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained("0xSero/INTELLECT-3-REAP-50", trust_remote_code=True)

messages = [{"role": "user", "content": "Write a Python function to calculate fibonacci numbers"}]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
outputs = model.generate(inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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