Summarization
GGUF
English
llama
text-summarization
text2text-generation
news
articles
minibase
standard-model
4096-context
Eval Results (legacy)
Instructions to use Minibase/Content-Preview-Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Minibase/Content-Preview-Generator with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Minibase/Content-Preview-Generator", filename="model.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Minibase/Content-Preview-Generator with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Minibase/Content-Preview-Generator # Run inference directly in the terminal: llama-cli -hf Minibase/Content-Preview-Generator
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Minibase/Content-Preview-Generator # Run inference directly in the terminal: llama-cli -hf Minibase/Content-Preview-Generator
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Minibase/Content-Preview-Generator # Run inference directly in the terminal: ./llama-cli -hf Minibase/Content-Preview-Generator
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Minibase/Content-Preview-Generator # Run inference directly in the terminal: ./build/bin/llama-cli -hf Minibase/Content-Preview-Generator
Use Docker
docker model run hf.co/Minibase/Content-Preview-Generator
- LM Studio
- Jan
- Ollama
How to use Minibase/Content-Preview-Generator with Ollama:
ollama run hf.co/Minibase/Content-Preview-Generator
- Unsloth Studio new
How to use Minibase/Content-Preview-Generator with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Minibase/Content-Preview-Generator to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Minibase/Content-Preview-Generator to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Minibase/Content-Preview-Generator to start chatting
- Docker Model Runner
How to use Minibase/Content-Preview-Generator with Docker Model Runner:
docker model run hf.co/Minibase/Content-Preview-Generator
- Lemonade
How to use Minibase/Content-Preview-Generator with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Minibase/Content-Preview-Generator
Run and chat with the model
lemonade run user.Content-Preview-Generator-{{QUANT_TAG}}List all available models
lemonade list
Upload generation_config.json with huggingface_hub
Browse files- generation_config.json +45 -0
generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": null,
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"do_sample": true,
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"max_length": 4096,
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"max_new_tokens": 256,
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"min_length": 0,
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"min_new_tokens": null,
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"early_stopping": false,
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"max_time": null,
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"num_beams": 1,
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"num_beam_groups": 1,
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"diversity_penalty": 0.0,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_scores": false,
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"return_dict_in_generate": false,
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"repetition_penalty": 1.0,
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"no_repeat_ngram_size": null,
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"renormalize_logits": false,
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"remove_invalid_values": false,
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"top_k": 40,
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"top_p": 0.9,
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"temperature": 0.3,
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"typical_p": 1.0,
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"epsilon_cutoff": 0.0,
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"eta_cutoff": 0.0,
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"diversity_penalty": 0.0,
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"num_return_sequences": 1,
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"length_penalty": 1.0,
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"bad_words_ids": null,
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"force_words_ids": null,
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"renormalize_logits": false,
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"constraints": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"remove_invalid_values": false,
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"exponential_decay_length_penalty": null,
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"suppress_tokens": null,
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"begin_suppress_tokens": null,
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"forced_decoder_ids": null
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}
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