neural-chat-7b-v1-1 / README.md
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metadata
license: apache-2.0

This model is a fine-tuned model for Chat based on mosaicml/mpt-7b with max_seq_lenght=2048 on the instruction-dataset-for-neural-chat-v1, databricks-dolly-15k, HC3 and oasst1 dataset.

Model date

Neural-chat-7b-v1.1 was trained on July 6, 2023.

Evaluation

We use the same evaluation metrics as open_llm_leaderboard which uses Eleuther AI Language Model Evaluation Harness, a unified framework to test generative language models on a large number of different evaluation tasks.

Model Average ⬆️ ARC (25-s) ⬆️ HellaSwag (10-s) ⬆️ MMLU (5-s) ⬆️ TruthfulQA (MC) (0-s) ⬆️
mosaicml/mpt-7b 47.4 47.61 77.56 31 33.43
mosaicml/mpt-7b-chat 49.95 46.5 75.55 37.60 40.17
Ours 51.41 50.09 76.69 38.79 40.07

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.02
  • num_epochs: 3.0

Inference with transformers

import transformers
model = transformers.AutoModelForCausalLM.from_pretrained(
  'Intel/neural-chat-7b-v1-1',
  trust_remote_code=True
)

Inference with INT8

Follow the instructions link to install the necessary dependencies. Use the below command to quantize the model using Intel Neural Compressor link and accelerate the inference.

python run_generation.py \
    --model Intel/neural-chat-7b-v1-1 \
    --quantize \
    --sq \
    --alpha 0.95 \
    --ipex

Organizations developing the model

The NeuralChat team with members from Intel/SATG/AIA/AIPT. Core team members: Kaokao Lv, Xuhui Ren, Liang Lv, Wenxin Zhang, and Haihao Shen.

Useful links

  • Intel Neural Compressor link
  • Intel Extension for Transformers link
  • Intel Extension for PyTorch link