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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- finetuned |
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- quantized |
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- 4-bit |
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- AWQ |
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- transformers |
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- pytorch |
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- mistral |
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- instruct |
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- text-generation |
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- conversational |
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- license:apache-2.0 |
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- autotrain_compatible |
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- endpoints_compatible |
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- text-generation-inference |
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- region:us |
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- finetune |
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- chatml |
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- RLHF |
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- gpt4 |
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- synthetic data |
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- distillation |
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datasets: |
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- allenai/ai2_arc |
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- allenai/ultrafeedback_binarized_cleaned |
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- argilla/distilabel-intel-orca-dpo-pairs |
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- jondurbin/airoboros-3.2 |
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- codeparrot/apps |
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- facebook/belebele |
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- bluemoon-fandom-1-1-rp-cleaned |
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- boolq |
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- camel-ai/biology |
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- camel-ai/chemistry |
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- camel-ai/math |
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- camel-ai/physics |
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- jondurbin/contextual-dpo-v0.1 |
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- jondurbin/gutenberg-dpo-v0.1 |
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- jondurbin/py-dpo-v0.1 |
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- jondurbin/truthy-dpo-v0.1 |
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- LDJnr/Capybara |
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- jondurbin/cinematika-v0.1 |
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- WizardLM/WizardLM_evol_instruct_70k |
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- glaiveai/glaive-function-calling-v2 |
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- jondurbin/gutenberg-dpo-v0.1 |
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- grimulkan/LimaRP-augmented |
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- lmsys/lmsys-chat-1m |
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- ParisNeo/lollms_aware_dataset |
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- TIGER-Lab/MathInstruct |
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- Muennighoff/natural-instructions |
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- openbookqa |
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- kingbri/PIPPA-shareGPT |
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- piqa |
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- Vezora/Tested-22k-Python-Alpaca |
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- ropes |
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- cakiki/rosetta-code |
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- Open-Orca/SlimOrca |
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- b-mc2/sql-create-context |
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- squad_v2 |
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- mattpscott/airoboros-summarization |
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- migtissera/Synthia-v1.3 |
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- unalignment/toxic-dpo-v0.2 |
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- WhiteRabbitNeo/WRN-Chapter-1 |
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- WhiteRabbitNeo/WRN-Chapter-2 |
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- winogrande |
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model_name: bagel 7B v0.4 |
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base_model: mistralai/Mistral-7B-v0.1 |
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quantized_by: Suparious |
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pipeline_tag: text-generation |
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model_creator: jondurbin |
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inference: false |
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prompt_template: '{bos}<|im_start|>{role} |
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{text} |
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<|im_end|>{eos} ' |
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--- |
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# A bagel, with everything (except DPO) |
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- Model creator: [jondurbin](https://huggingface.co/jondurbin) |
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- Original model: [bagel-7b-v0.4](https://huggingface.co/jondurbin/bagel-7b-v0.4) |
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![bagel](bagel.png) |
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## Model Description |
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This is the pre-DPO version of the mistral-7b model fine-tuned with https://github.com/jondurbin/bagel |
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The DPO counterpart is available here: https://huggingface.co/solidrust/bagel-dpo-7b-v0.4-AWQ |
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The non-DPO version is likely better for roleplay usage. |
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Compute generously provided by [MassedCompute](https://massedcompute.com/?utm_source=huggingface&utm_creative_format=model_card&utm_content=creator_jon) |
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## How to use |
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### Install the necessary packages |
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```bash |
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pip install --upgrade autoawq autoawq-kernels |
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``` |
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### Example Python code |
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```python |
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from awq import AutoAWQForCausalLM |
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from transformers import AutoTokenizer, TextStreamer |
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model_path = "solidrust/bagel-7b-v0.4-AWQ" |
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system_message = "You are Bagel, incarnated a powerful AI with everything." |
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# Load model |
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model = AutoAWQForCausalLM.from_quantized(model_path, |
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fuse_layers=True) |
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tokenizer = AutoTokenizer.from_pretrained(model_path, |
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trust_remote_code=True) |
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streamer = TextStreamer(tokenizer, |
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skip_prompt=True, |
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skip_special_tokens=True) |
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# Convert prompt to tokens |
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prompt_template = """\ |
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<|im_start|>system |
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{system_message}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant""" |
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prompt = "You're standing on the surface of the Earth. "\ |
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"You walk one mile south, one mile west and one mile north. "\ |
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"You end up exactly where you started. Where are you?" |
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tokens = tokenizer(prompt_template.format(system_message=system_message,prompt=prompt), |
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return_tensors='pt').input_ids.cuda() |
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# Generate output |
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generation_output = model.generate(tokens, |
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streamer=streamer, |
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max_new_tokens=512) |
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``` |
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### About AWQ |
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AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings. |
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AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead. |
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It is supported by: |
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- [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ |
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- [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types. |
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- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference) |
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- [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers |
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- [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code |
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## Prompt template: ChatML |
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```plaintext |
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<|im_start|>system |
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{system_message}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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``` |
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