Instructions to use fakezeta/neural-chat-7b-v3-1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use fakezeta/neural-chat-7b-v3-1-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
Use Docker
docker model run hf.co/fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use fakezeta/neural-chat-7b-v3-1-GGUF with Ollama:
ollama run hf.co/fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
- Unsloth Desktop
- Docker Model Runner
How to use fakezeta/neural-chat-7b-v3-1-GGUF with Docker Model Runner:
docker model run hf.co/fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
- Lemonade
How to use fakezeta/neural-chat-7b-v3-1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull fakezeta/neural-chat-7b-v3-1-GGUF:Q5_K_M
Run and chat with the model
lemonade run user.neural-chat-7b-v3-1-GGUF-Q5_K_M
List all available models
lemonade list
- Atomic Chat
Upload 2 files
Browse files- .gitattributes +1 -0
- README.md +76 -0
- neural-chat-7b-v3-1_Q5_K_M.gguf +3 -0
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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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---
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neural-chat-7b-v3-1 - GGUF
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Model creator: [Intel](https://huggingface.co/Intel)
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Original model: [neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1)
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Description
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This repo contains GGUF format model files for Intel's neural-chat-7b-v3-1.
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These files were quantised with Q5_K_M.
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## Original Readme from Intel
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## Finetuning on [habana](https://habana.ai/) HPU
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This model is a fine-tuned model based on [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the open source dataset [Open-Orca/SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca). Then we align it with DPO algorithm. For more details, you can refer our blog: [NeuralChat: Simplifying Supervised Instruction Fine-Tuning and Reinforcement Aligning](https://medium.com/intel-analytics-software/neuralchat-simplifying-supervised-instruction-fine-tuning-and-reinforcement-aligning-for-chatbots-d034bca44f69).
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## Model date
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Neural-chat-7b-v3 was trained between September and October, 2023.
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## Evaluation
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We submit our model to [open_llm_leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard), and the model performance has been **improved significantly** as we see from the average metric of 7 tasks from the leaderboard.
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| Model | Average ⬆️| ARC (25-s) ⬆️ | HellaSwag (10-s) ⬆️ | MMLU (5-s) ⬆️| TruthfulQA (MC) (0-s) ⬆️ | Winogrande (5-s) | GSM8K (5-s) | DROP (3-s) |
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| --- | --- | --- | --- | --- | --- | --- | --- | --- |
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|[mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 50.32 | 59.58 | 83.31 | 64.16 | 42.15 | 78.37 | 18.12 | 6.14 |
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| [Intel/neural-chat-7b-v3](https://huggingface.co/Intel/neural-chat-7b-v3) | **57.31** | 67.15 | 83.29 | 62.26 | 58.77 | 78.06 | 1.21 | 50.43 |
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| [Intel/neural-chat-7b-v3-1](https://huggingface.co/Intel/neural-chat-7b-v3-1) | **59.06** | 66.21 | 83.64 | 62.37 | 59.65 | 78.14 | 19.56 | 43.84 |
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-04
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- train_batch_size: 1
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-HPU
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- num_devices: 8
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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- total_eval_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.02
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- num_epochs: 2.0
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## Inference with transformers
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```shell
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import transformers
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model = transformers.AutoModelForCausalLM.from_pretrained(
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'Intel/neural-chat-7b-v3'
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)
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```
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## Ethical Considerations and Limitations
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neural-chat-7b-v3 can produce factually incorrect output, and should not be relied on to produce factually accurate information. neural-chat-7b-v3 was trained on [Open-Orca/SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca) based on [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). Because of the limitations of the pretrained model and the finetuning datasets, it is possible that this model could generate lewd, biased or otherwise offensive outputs.
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Therefore, before deploying any applications of neural-chat-7b-v3, developers should perform safety testing.
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## Disclaimer
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The license on this model does not constitute legal advice. We are not responsible for the actions of third parties who use this model. Please cosult an attorney before using this model for commercial purposes.
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## Organizations developing the model
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The NeuralChat team with members from Intel/SATG/AIA/AIPT. Core team members: Kaokao Lv, Liang Lv, Chang Wang, Wenxin Zhang, Xuhui Ren, and Haihao Shen.
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## Useful links
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* Intel Neural Compressor [link](https://github.com/intel/neural-compressor)
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* Intel Extension for Transformers [link](https://github.com/intel/intel-extension-for-transformers)
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* Intel Extension for PyTorch [link](https://github.com/intel/intel-extension-for-pytorch)
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version https://git-lfs.github.com/spec/v1
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oid sha256:71ccc0ba42e2ac86f593d7905f9be865e3870496ade370537ae1db0c13637bc1
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size 5131409024
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