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--- |
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license: apache-2.0 |
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datasets: |
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- nomic-ai/gpt4all-j-prompt-generations |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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# Model Card for GPT4All-Falcon |
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An Apache-2 licensed chatbot trained over a massive curated corpus of assistant interactions including word problems, multi-turn dialogue, code, poems, songs, and stories. |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This model has been finetuned from [Falcon](https://huggingface.co/tiiuae/falcon-7b) |
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- **Developed by:** [Nomic AI](https://home.nomic.ai) |
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- **Model Type:** A finetuned Falcon 7B model on assistant style interaction data |
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- **Language(s) (NLP):** English |
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- **License:** Apache-2 |
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- **Finetuned from model [optional]:** [Falcon](https://huggingface.co/tiiuae/falcon-7b) |
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To download a model with a specific revision run |
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```python |
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from transformers import AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained("nomic-ai/gpt4all-falcon", trust_remote_code=True) |
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``` |
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Downloading without specifying `revision` defaults to `main`/`v1.0`. |
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To use it for inference with Cuda, run |
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```python |
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from transformers import AutoTokenizer, pipeline |
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import transformers |
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import torch |
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False) |
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model.to("cuda:0") |
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prompt = "Describe a painting of a falcon in a very detailed way." # Change this to your prompt |
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prompt_template = f"### Instruction: {prompt}\n### Response:" |
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tokens = tokenizer(prompt_template, return_tensors="pt").input_ids.to("cuda:0") |
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output = model.generate(input_ids=tokens, max_new_tokens=256, do_sample=True, temperature=0.8) |
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# Print the generated text |
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print(tokenizer.decode(output[0])) |
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``` |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [https://github.com/nomic-ai/gpt4all](https://github.com/nomic-ai/gpt4all) |
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- **Base Model Repository:** [https://huggingface.co/tiiuae/falcon-7b](https://huggingface.co/tiiuae/falcon-7b) |
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- **Demo [optional]:** [https://gpt4all.io/](https://gpt4all.io/) |
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### Training Procedure |
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GPT4All is made possible by our compute partner [Paperspace](https://www.paperspace.com/). |
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Trained on a DGX cluster with 8 A100 80GB GPUs for ~12 hours. Using Deepspeed + Accelerate, we use a global batch size of 256 with a learning rate of 2e-5. More information can be found in the repo. |
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### Results |
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Results on common sense reasoning benchmarks |
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``` |
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| Model | BoolQ | PIQA | HellaSwag | WinoGrande | ARC-e | ARC-c | OBQA | Avg. | |
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|:--------------------------|:--------:|:--------:|:---------:|:----------:|:--------:|:--------:|:--------:|:--------:| |
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| GPT4All-J 6B v1.0 | 73.4 | 74.8 | 63.4 | 64.7 | 54.9 | 36.0 | 40.2 | 58.2 | |
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| GPT4All-J v1.1-breezy | 74.0 | 75.1 | 63.2 | 63.6 | 55.4 | 34.9 | 38.4 | 57.8 | |
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| GPT4All-J v1.2-jazzy | 74.8 | 74.9 | 63.6 | 63.8 | 56.6 | 35.3 | 41.0 | 58.6 | |
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| GPT4All-J v1.3-groovy | 73.6 | 74.3 | 63.8 | 63.5 | 57.7 | 35.0 | 38.8 | 58.1 | |
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| GPT4All-J Lora 6B | 68.6 | 75.8 | 66.2 | 63.5 | 56.4 | 35.7 | 40.2 | 58.1 | |
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| GPT4All LLaMa Lora 7B | 73.1 | 77.6 | 72.1 | 67.8 | 51.1 | 40.4 | 40.2 | 60.3 | |
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| GPT4All 13B snoozy | **83.3** | 79.2 | 75.0 | **71.3** | 60.9 | 44.2 | 43.4 | 65.3 | |
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| GPT4All Falcon | 77.6 | 79.8 | 74.9 | 70.1 | 67.9 | 43.4 | 42.6 | 65.2 | |
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| Dolly 6B | 68.8 | 77.3 | 67.6 | 63.9 | 62.9 | 38.7 | 41.2 | 60.1 | |
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| Dolly 12B | 56.7 | 75.4 | 71.0 | 62.2 | 64.6 | 38.5 | 40.4 | 58.4 | |
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| Alpaca 7B | 73.9 | 77.2 | 73.9 | 66.1 | 59.8 | 43.3 | 43.4 | 62.4 | |
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| Alpaca Lora 7B | 74.3 | 79.3 | 74.0 | 68.8 | 56.6 | 43.9 | 42.6 | 62.8 | |
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| GPT-J 6.7B | 65.4 | 76.2 | 66.2 | 64.1 | 62.2 | 36.6 | 38.2 | 58.4 | |
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| LLama 7B | 73.1 | 77.4 | 73.0 | 66.9 | 52.5 | 41.4 | 42.4 | 61.0 | |
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| LLama 13B | 68.5 | 79.1 | 76.2 | 70.1 | 60.0 | **44.6** | 42.2 | 63.0 | |
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| Pythia 6.7B | 63.5 | 76.3 | 64.0 | 61.1 | 61.3 | 35.2 | 37.2 | 57.0 | |
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| Pythia 12B | 67.7 | 76.6 | 67.3 | 63.8 | 63.9 | 34.8 | 38 | 58.9 | |
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| Fastchat T5 | 81.5 | 64.6 | 46.3 | 61.8 | 49.3 | 33.3 | 39.4 | 53.7 | |
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| Fastchat Vicuña 7B | 76.6 | 77.2 | 70.7 | 67.3 | 53.5 | 41.2 | 40.8 | 61.0 | |
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| Fastchat Vicuña 13B | 81.5 | 76.8 | 73.3 | 66.7 | 57.4 | 42.7 | 43.6 | 63.1 | |
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| StableVicuña RLHF | 82.3 | 78.6 | 74.1 | 70.9 | 61.0 | 43.5 | **44.4** | 65.0 | |
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| StableLM Tuned | 62.5 | 71.2 | 53.6 | 54.8 | 52.4 | 31.1 | 33.4 | 51.3 | |
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| StableLM Base | 60.1 | 67.4 | 41.2 | 50.1 | 44.9 | 27.0 | 32.0 | 42.2 | |
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| Koala 13B | 76.5 | 77.9 | 72.6 | 68.8 | 54.3 | 41.0 | 42.8 | 62.0 | |
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| Open Assistant Pythia 12B | 67.9 | 78.0 | 68.1 | 65.0 | 64.2 | 40.4 | 43.2 | 61.0 | |
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| Mosaic MPT7B | 74.8 | 79.3 | 76.3 | 68.6 | 70.0 | 42.2 | 42.6 | 64.8 | |
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| Mosaic mpt-instruct | 74.3 | 80.4 | **77.2** | 67.8 | **72.2** | **44.6** | 43.0 | **65.6** | |
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| Mosaic mpt-chat | 77.1 | 78.2 | 74.5 | 67.5 | 69.4 | 43.3 | 44.2 | 64.9 | |
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| Wizard 7B | 78.4 | 77.2 | 69.9 | 66.5 | 56.8 | 40.5 | 42.6 | 61.7 | |
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| Wizard 7B Uncensored | 77.7 | 74.2 | 68.0 | 65.2 | 53.5 | 38.7 | 41.6 | 59.8 | |
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| Wizard 13B Uncensored | 78.4 | 75.5 | 72.1 | 69.5 | 57.5 | 40.4 | 44.0 | 62.5 | |
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| GPT4-x-Vicuna-13b | 81.3 | 75.0 | 75.2 | 65.0 | 58.7 | 43.9 | 43.6 | 62.2 | |
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| Falcon 7b | 73.6 | **80.7** | 76.3 | 67.3 | 71.0 | 43.3 | 44.4 | 65.2 | |
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| text-davinci-003 | 88.1 | 83.8 | 83.4 | 75.8 | 83.9 | 63.9 | 51.0 | 75.7 | |
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``` |
