| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | datasets: |
| | - togethercomputer/RedPajama-Data-1T |
| | - OpenAssistant/oasst1 |
| | - databricks/databricks-dolly-15k |
| | widget: |
| | - text: "<human>: Write an email to my friends inviting them to come to my home on Friday for a dinner party, bring their own food to share.\n<bot>:" |
| | example_title: "Email Writing" |
| | - text: "<human>: Create a list of things to do in San Francisco\n<bot>:" |
| | example_title: "Brainstorming" |
| | inference: |
| | parameters: |
| | temperature: 0.7 |
| | top_p: 0.7 |
| | top_k: 50 |
| | max_new_tokens: 128 |
| | --- |
| | |
| | # RedPajama-INCITE-Chat-7B-v0.1 |
| |
|
| | RedPajama-INCITE-Chat-7B-v0.1 was developed by Together and leaders from the open-source AI community including Ontocord.ai, ETH DS3Lab, AAI CERC, Université de Montréal, MILA - Québec AI Institute, Stanford Center for Research on Foundation Models (CRFM), Stanford Hazy Research research group and LAION. |
| |
|
| | It is fine-tuned on OASST1 and Dolly2 to enhance chatting ability. |
| |
|
| | ## Model Details |
| | - **Developed by**: Together Computer. |
| | - **Model type**: Language Model |
| | - **Language(s)**: English |
| | - **License**: Apache 2.0 |
| | - **Model Description**: A 6.9B parameter pretrained language model. |
| |
|
| | # Quick Start |
| |
|
| | Please note that the model requires `transformers` version >= 4.25.1. |
| |
|
| | To prompt the chat model, use the following format: |
| | ``` |
| | <human>: [Instruction] |
| | <bot>: |
| | ``` |
| |
|
| | ## GPU Inference |
| |
|
| | This requires a GPU with 16GB memory. |
| |
|
| | ```python |
| | import torch |
| | import transformers |
| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | |
| | MIN_TRANSFORMERS_VERSION = '4.25.1' |
| | |
| | # check transformers version |
| | assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.' |
| | |
| | # init |
| | tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1") |
| | model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1", torch_dtype=torch.float16) |
| | model = model.to('cuda:0') |
| | # infer |
| | prompt = "<human>: Who is Alan Turing?\n<bot>:" |
| | inputs = tokenizer(prompt, return_tensors='pt').to(model.device) |
| | input_length = inputs.input_ids.shape[1] |
| | outputs = model.generate( |
| | **inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True |
| | ) |
| | token = outputs.sequences[0, input_length:] |
| | output_str = tokenizer.decode(token) |
| | print(output_str) |
| | """ |
| | Alan Mathison Turing (23 June 1912 7 June 1954) was an English computer scientist, mathematician, logician, cryptanalyst, philosopher, mathematician, and theoretical biologist. |
| | """ |
| | ``` |
| |
|
| | ## GPU Inference in Int8 |
| |
|
| | This requires a GPU with 12GB memory. |
| |
|
| | To run inference with int8, please ensure you have installed accelerate and bitandbytes. You can install them with the following command: |
| |
|
| | ```bash |
| | pip install accelerate |
| | pip install bitsandbytes |
| | ``` |
| |
|
| | Then you can run inference with int8 as follows: |
| |
|
| | ```python |
| | import torch |
| | import transformers |
| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | |
| | MIN_TRANSFORMERS_VERSION = '4.25.1' |
| | |
| | # check transformers version |
| | assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.' |
| | |
| | # init |
| | tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1") |
| | model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1", device_map='auto', torch_dtype=torch.float16, load_in_8bit=True) |
| | |
| | # infer |
| | prompt = "<human>: Who is Alan Turing?\n<bot>:" |
| | inputs = tokenizer(prompt, return_tensors='pt').to(model.device) |
| | input_length = inputs.input_ids.shape[1] |
| | outputs = model.generate( |
| | **inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True |
| | ) |
| | token = outputs.sequences[0, input_length:] |
| | output_str = tokenizer.decode(token) |
| | print(output_str) |
| | """ |
| | Alan Mathison Turing (23 June 1912 – 7 June 1954) was an English computer scientist, mathematician, logician, cryptanalyst, philosopher, and theoretical biologist. |
| | """ |
| | ``` |
| |
|
| | ## CPU Inference |
| |
|
| | ```python |
| | import torch |
| | import transformers |
| | from transformers import AutoTokenizer, AutoModelForCausalLM |
| | |
| | MIN_TRANSFORMERS_VERSION = '4.25.1' |
| | |
| | # check transformers version |
| | assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.' |
| | |
| | # init |
| | tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1") |
| | model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Chat-7B-v0.1", torch_dtype=torch.bfloat16) |
| | # infer |
| | prompt = "<human>: Who is Alan Turing?\n<bot>:" |
| | inputs = tokenizer(prompt, return_tensors='pt').to(model.device) |
| | input_length = inputs.input_ids.shape[1] |
| | outputs = model.generate( |
| | **inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True |
| | ) |
| | token = outputs.sequences[0, input_length:] |
| | output_str = tokenizer.decode(token) |
| | print(output_str) |
| | """ |
| | Alan Mathison Turing, OBE, FRS, (23 June 1912 – 7 June 1954) was an English computer scientist, mathematician, logician, cryptanalyst, philosopher, and theoretical biologist. |
| | """ |
| | ``` |
| |
|
| | Please note that since `LayerNormKernelImpl` is not implemented in fp16 for CPU, we use `bfloat16` for CPU inference. |
| |
|
| |
|
| | # Uses |
| |
|
| | ## Direct Use |
| |
|
| | Excluded uses are described below. |
| |
|
| | ### Misuse, Malicious Use, and Out-of-Scope Use |
| |
|
| | It is the responsibility of the end user to ensure that the model is used in a responsible and ethical manner. |
| |
|
| | #### Out-of-Scope Use |
| |
|
| | `RedPajama-INCITE-Chat-7B-v0.1` is a language model and may not perform well for other use cases outside of its intended scope. |
| | For example, it may not be suitable for use in safety-critical applications or for making decisions that have a significant impact on individuals or society. |
| | It is important to consider the limitations of the model and to only use it for its intended purpose. |
| |
|
| | #### Misuse and Malicious Use |
| |
|
| | `RedPajama-INCITE-Chat-7B-v0.1` is designed for language modeling. |
| | Misuse of the model, such as using it to engage in illegal or unethical activities, is strictly prohibited and goes against the principles of the project. |
| |
|
| | Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to: |
| |
|
| | - Generating fake news, misinformation, or propaganda |
| | - Promoting hate speech, discrimination, or violence against individuals or groups |
| | - Impersonating individuals or organizations without their consent |
| | - Engaging in cyberbullying or harassment |
| | - Defamatory content |
| | - Spamming or scamming |
| | - Sharing confidential or sensitive information without proper authorization |
| | - Violating the terms of use of the model or the data used to train it |
| | - Creating automated bots for malicious purposes such as spreading malware, phishing scams, or spamming |
| |
|
| | ## Limitations |
| |
|
| | `RedPajama-INCITE-Chat-7B-v0.1`, like other language models, has limitations that should be taken into consideration. |
| | For example, the model may not always provide accurate or relevant answers, particularly for questions that are complex, ambiguous, or outside of its training data. |
| | We therefore welcome contributions from individuals and organizations, and encourage collaboration towards creating a more robust and inclusive chatbot. |
| |
|
| | ## Training |
| |
|
| | **Training Data** |
| |
|
| | Please refer to [togethercomputer/RedPajama-Data-1T](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) |
| |
|
| | **Training Procedure** |
| |
|
| | - **Hardware:** 8 A100 |
| | - **Optimizer:** Adam |
| | - **Gradient Accumulations**: 1 |
| | - **Num of Tokens:** 131M tokens |
| | - **Learning rate:** 1e-5 |
| |
|
| | ## Community |
| |
|
| | Join us on [Together Discord](https://discord.gg/6ZVDU8tTD4) |