Instructions to use Triangles/gpt-Neo_Russell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Triangles/gpt-Neo_Russell with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Triangles/gpt-Neo_Russell")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Triangles/gpt-Neo_Russell") model = AutoModelForCausalLM.from_pretrained("Triangles/gpt-Neo_Russell", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Triangles/gpt-Neo_Russell with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Triangles/gpt-Neo_Russell" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Triangles/gpt-Neo_Russell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Triangles/gpt-Neo_Russell
- SGLang
How to use Triangles/gpt-Neo_Russell with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Triangles/gpt-Neo_Russell" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Triangles/gpt-Neo_Russell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Triangles/gpt-Neo_Russell" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Triangles/gpt-Neo_Russell", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Triangles/gpt-Neo_Russell with Docker Model Runner:
docker model run hf.co/Triangles/gpt-Neo_Russell
|
Download README.md from Triangles/gpt-Neo_Russell: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Triangles/gpt-Neo_Russell/resolve/main/README.md
- Command line
-
hf download hf://Triangles/gpt-Neo_Russell/README.md
-
curl -L -o README.md https://huggingface.co/Triangles/gpt-Neo_Russell/resolve/main/README.md
4.92 kB
| license: cc-by-nc-sa-4.0 | |
| language: | |
| - en | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| This is a gpt_neo (125M) text generation model fine-tuned on a single book: Bertant Russell's The Problems of Philosophy, from 1912. | |
| # Model Details | |
| ## Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** [More Information Needed] | |
| - **Shared by [optional]:** [More Information Needed] | |
| - **Model type:** [More Information Needed] | |
| - **Language(s) (NLP):** [More Information Needed] | |
| - **License:** [More Information Needed] | |
| - **Finetuned from model [optional]:** [More Information Needed] | |
| ## Model Sources [optional] | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** [More Information Needed] | |
| - **Paper [optional]:** [More Information Needed] | |
| - **Demo [optional]:** [More Information Needed] | |
| # Uses | |
| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> | |
| ## Direct Use | |
| <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> | |
| [More Information Needed] | |
| ## Downstream Use [optional] | |
| <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> | |
| [More Information Needed] | |
| ## Out-of-Scope Use | |
| <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> | |
| [More Information Needed] | |
| # Bias, Risks, and Limitations | |
| <!-- This section is meant to convey both technical and sociotechnical limitations. --> | |
| [More Information Needed] | |
| ## Recommendations | |
| <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> | |
| Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. | |
| # Training Details | |
| ## Training Data | |
| <!-- This should link to a Data 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. --> | |
| [More Information Needed] | |
| ## Training Procedure [optional] | |
| <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> | |
| ### Preprocessing | |
| [More Information Needed] | |
| ### Speeds, Sizes, Times | |
| <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> | |
| [More Information Needed] | |
| # Evaluation | |
| <!-- This section describes the evaluation protocols and provides the results. --> | |
| ## Testing Data, Factors & Metrics | |
| ### Testing Data | |
| <!-- This should link to a Data Card if possible. --> | |
| [More Information Needed] | |
| ### Factors | |
| <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> | |
| [More Information Needed] | |
| ### Metrics | |
| <!-- These are the evaluation metrics being used, ideally with a description of why. --> | |
| [More Information Needed] | |
| ## Results | |
| [More Information Needed] | |
| ### Summary | |
| # Model Examination [optional] | |
| <!-- Relevant interpretability work for the model goes here --> | |
| [More Information Needed] | |
| # Environmental Impact | |
| <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> | |
| 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). | |
| - **Hardware Type:** [More Information Needed] | |
| - **Hours used:** [More Information Needed] | |
| - **Cloud Provider:** [More Information Needed] | |
| - **Compute Region:** [More Information Needed] | |
| - **Carbon Emitted:** [More Information Needed] | |
| # Technical Specifications [optional] | |
| ## Model Architecture and Objective | |
| [More Information Needed] | |
| ## Compute Infrastructure | |
| [More Information Needed] | |
| ### Hardware | |
| [More Information Needed] | |
| ### Software | |
| [More Information Needed] | |
| # Citation [optional] | |
| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> | |
| **BibTeX:** | |
| [More Information Needed] | |
| **APA:** | |
| [More Information Needed] | |
| # Glossary [optional] | |
| <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> | |
| [More Information Needed] | |
| # More Information [optional] | |
| [More Information Needed] | |
| # Model Card Authors [optional] | |
| [More Information Needed] | |
| # Model Card Contact | |
| [More Information Needed] | |
| # How to Get Started with the Model | |
| Use the code below to get started with the model. | |
| <details> | |
| <summary> Click to expand </summary> | |
| [More Information Needed] | |
| </details> |