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--- |
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license: apache-2.0 |
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language: |
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- en |
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- de |
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- es |
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- fr |
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tags: |
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- sft |
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inference: false |
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datasets: |
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- OpenAssistant/oasst1 |
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--- |
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[]() |
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## I am still building the structure of these descriptions. |
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These will contain increasingly more content to help find the best models for a purpose. |
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# falcon-40b-sft-top1-560 - GGUF |
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- Model creator: [OpenAssistant](https://huggingface.co/OpenAssistant) |
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- Original model: [falcon-40b-sft-top1-560](https://huggingface.co/OpenAssistant/falcon-40b-sft-top1-560) |
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# About GGUF format |
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`gguf` is the current file format used by the [`ggml`](https://github.com/ggerganov/ggml) library. |
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A growing list of Software is using it and can therefore use this model. |
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The core project making use of the ggml library is the [llama.cpp](https://github.com/ggerganov/llama.cpp) project by Georgi Gerganov |
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# Quantization variants |
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There is a bunch of quantized files available. How to choose the best for you: |
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# legacy quants |
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Q4_0, Q4_1, Q5_0, Q5_1 and Q8 are `legacy` quantization types. |
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Nevertheless, they are fully supported, as there are several circumstances that cause certain model not to be compatible with the modern K-quants. |
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Falcon 7B models cannot be quantized to K-quants. |
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# K-quants |
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K-quants are based on the idea that the quantization of certain parts affects the quality in different ways. If you quantize certain parts more and others less, you get a more powerful model with the same file size, or a smaller file size and lower memory load with comparable performance. |
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So, if possible, use K-quants. |
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With a Q6_K you should find it really hard to find a quality difference to the original model - ask your model two times the same question and you may encounter bigger quality differences. |
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# Original Model Card: |
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# Open-Assistant Falcon 40B SFT OASST-TOP1 Model |
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This model is a fine-tuning of TII's [Falcon 40B](https://huggingface.co/tiiuae/falcon-40b) LLM. |
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It was trained with top-1 (high-quality) demonstrations of the OASST data set (exported on May 6, 2023) with an effective batch size of 144 for ~7.5 epochs with LIMA style dropout (p=0.3) and a context-length of 2048 tokens. |
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## Model Details |
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- **Finetuned from:** [tiiuae/falcon-40b]((https://huggingface.co/tiiuae/falcon-40b) |
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- **Model type:** Causal decoder-only transformer language model |
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- **Language:** English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish); |
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- **Demo:** [Continuations for 250 random prompts](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Fchat-gpt%2F2023-04-11_gpt-3.5-turbo_lottery.json%0Ahttps%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-sft%2F2023-06-03_OpenAssistant_falcon-40b-sft-top1-560_sampling_noprefix2.json) |
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- **Eval results:** [ilm-eval](https://tju01.github.io/ilm-eval/) |
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- **Weights & Biases**: [Training log](https://wandb.ai/open-assistant/public-sft/runs/3lr77x4h) (Checkpoint: 560 steps) |
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- **License:** Apache 2.0 |
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- **Contact:** [Open-Assistant Discord](https://ykilcher.com/open-assistant-discord) |
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## Prompting |
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Two special tokens are used to mark the beginning of user and assistant turns: |
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`<|prompter|>` and `<|assistant|>`. Each turn ends with a `<|endoftext|>` token. |
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Input prompt example: |
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``` |
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<|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|> |
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``` |
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The input ends with the `<|assistant|>` token to signal that the model should |
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start generating the assistant reply. |
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## Configuration Details |
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Model: |
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``` |
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falcon-40b: |
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dtype: bf16 |
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log_dir: "falcon_log_40b" |
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learning_rate: 5e-6 |
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model_name: "tiiuae/falcon-40b" |
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deepspeed_config: configs/zero3_config_falcon.json |
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output_dir: falcon |
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weight_decay: 0.0 |
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max_length: 2048 |
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warmup_steps: 20 |
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gradient_checkpointing: true |
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gradient_accumulation_steps: 1 |
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per_device_train_batch_size: 18 |
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per_device_eval_batch_size: 10 |
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eval_steps: 80 |
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save_steps: 80 |
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num_train_epochs: 8 |
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save_total_limit: 4 |
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use_flash_attention: false |
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residual_dropout: 0.3 |
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residual_dropout_lima: true |
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sort_by_length: false |
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save_strategy: steps |
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``` |
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Dataset: |
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``` |
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oasst-top1: |
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datasets: |
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- oasst_export: |
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lang: "bg,ca,cs,da,de,en,es,fr,hr,hu,it,nl,pl,pt,ro,ru,sl,sr,sv,uk" # sft-8.0 |
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input_file_path: 2023-05-06_OASST_labels.jsonl.gz |
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val_split: 0.05 |
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top_k: 1 |
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```<center> |
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[](https://maddes8cht.github.io) |
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[](https://stackexchange.com/users/26485911) |
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[](https://github.com/maddes8cht) |
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[](https://huggingface.co/maddes8cht) |
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[](https://twitter.com/maddes1966) |
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</center> |
