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--- |
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library_name: transformers |
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license: apache-2.0 |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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Builds on the falcon 7b instruct shared model, the specific model is linked in the model description section. |
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Trained using this [mental health dataset](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations) |
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How to test the model |
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```python |
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import json |
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import os |
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from pprint import pprint |
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import bitsandbytes as bnb |
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import torch |
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import torch.nn as nn |
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import transformers |
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from datasets import load_dataset |
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from huggingface_hub import notebook_login |
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from peft import ( |
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LoraConfig, |
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PeftConfig, |
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PeftModel, |
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get_peft_model, |
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prepare_model_for_kbit_training |
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) |
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from transformers import ( |
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AutoConfig, |
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AutoModelForCausalLM, |
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AutoTokenizer, |
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BitsAndBytesConfig |
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) |
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os.environ["CUDA_VISIBLE_DEVICES"] = "0" |
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PEFT_MODEL = "akumar23/mental-falcon-7b" |
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bnb_config = BitsAndBytesConfig( |
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load_in_4bit=True, |
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bnb_4bit_use_double_quant=True, |
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bnb_4bit_quant_type="nf4", |
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bnb_4bit_compute_dtype=torch.bfloat16 |
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) |
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config = PeftConfig.from_pretrained(PEFT_MODEL) |
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model = AutoModelForCausalLM.from_pretrained( |
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config.base_model_name_or_path, |
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return_dict=True, |
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quantization_config=bnb_config, |
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device_map="auto", |
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trust_remote_code=True |
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) |
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tokenizer=AutoTokenizer.from_pretrained(config.base_model_name_or_path) |
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tokenizer.pad_token = tokenizer.eos_token |
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model = PeftModel.from_pretrained(model, PEFT_MODEL) |
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generation_config = model.generation_config |
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generation_config.max_new_tokens = 200 |
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generation_config.temperature = 0.7 |
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generation_config.top_p = 0.7 |
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generation_config.num_return_sequences = 1 |
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generation_config.pad_token_id = tokenizer.eos_token_id |
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generation_config.eos_token_id = tokenizer.eos_token_id |
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device = "cuda:0" |
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prompt = """ |
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<human>: how do i know if i am depressed |
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<assistant>: |
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""".strip() |
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encoding = tokenizer(prompt, return_tensors="pt").to(device) |
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with torch.inference_mode(): |
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outputs = model.generate( |
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input_ids = encoding.input_ids, |
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attention_mask = encoding.attention_mask, |
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generation_config = generation_config |
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) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
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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 is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** [Aryan Kumar](https://www.linkedin.com/in/aryan-kumar-9640b4150); |
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- **Model type:** Causal decoder-only; |
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- **Language(s) (NLP):** English and French; |
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- **License:** Apache 2.0; |
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- **Finetuned from model:** [falcon-7b-instruct-sharded](https://huggingface.co/vilsonrodrigues/falcon-7b-instruct-sharded). |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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[More Information Needed] |
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### Downstream Use [optional] |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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[More Information Needed] |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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<!-- This should link to a Dataset Card if possible. --> |
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[More Information Needed] |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
