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--- |
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library_name: transformers |
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tags: [] |
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--- |
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# Model Card for X-LoRA-Gemma-7b |
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<!-- Provide a quick summary of what the model is/does. --> |
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``` |
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import torch |
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from xlora.xlora_utils import load_model |
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XLoRa_model_name = 'lamm-mit/x-lora-gemma-7b' |
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model,tokenizer=load_model(model_name = XLoRa_model_name, |
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device='cuda:0', |
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use_flash_attention_2=True, |
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dtype=torch.bfloat16, |
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) |
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eos_token_id= tokenizer('<end_of_turn>', add_special_tokens=False, ) ['input_ids'][0] |
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``` |
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``` |
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def generate_XLoRA_Gemma (system_prompt='You a helpful assistant. You are familiar with materials science. ', |
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prompt='What is spider silk in the context of bioinspired materials?', |
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repetition_penalty=1.,num_beams=1,num_return_sequences=1, |
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top_p=0.9, top_k=256, temperature=.5,max_new_tokens=512, verbatim=False, eos_token=None, |
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add_special_tokens=True, prepend_response='', |
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): |
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if eos_token==None: |
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eos_token= tokenizer.eos_token_id |
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if system_prompt==None: |
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messages=[ {"role": "user", "content": prompt}, ] |
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else: |
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messages=[ {"role": "user", "content": system_prompt+prompt}, ] |
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txt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True, ) |
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txt=txt+prepend_response |
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inputs = tokenizer(txt, add_special_tokens =add_special_tokens, return_tensors ='pt').to(device) |
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with torch.no_grad(): |
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outputs = model.generate(input_ids = inputs["input_ids"], |
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attention_mask = inputs["attention_mask"] , # This is usually done automatically by the tokenizer |
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max_new_tokens=max_new_tokens, |
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temperature=temperature, #value used to modulate the next token probabilities. |
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num_beams=num_beams, |
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top_k = top_k, |
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top_p = top_p, |
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num_return_sequences = num_return_sequences, |
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eos_token_id=eos_token, |
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pad_token_id = eos_token, |
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do_sample =True,#skip_prompt=True, |
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repetition_penalty=repetition_penalty, |
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) |
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return tokenizer.batch_decode(outputs[:,inputs["input_ids"].shape[1]:].detach().cpu().numpy(), skip_special_tokens=True) |
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``` |
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Then, use as follows: |
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``` |
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from IPython.display import display, Markdown |
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q='''What is graphene?''' |
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res=generate_XLoRA_Gemma( system_prompt='You design materials.', prompt=q, max_new_tokens=1024, temperature=0.3, eos_token=eos_token_id) |
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display (Markdown(res)) |
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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:** [More Information Needed] |
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- **Funded by [optional]:** [More Information Needed] |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** [More Information Needed] |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** [More Information Needed] |
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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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## 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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## Model Card Contact |
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