Instructions to use Minibase/Content-Preview-Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

Content-Preview-Generator / generation_config.json

Minibase

Upload generation_config.json with huggingface_hub

bcd9d1c verified 8 months ago

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	{
	"_from_model_config": true,
	"bos_token_id": 1,
	"eos_token_id": 2,
	"pad_token_id": null,
	"do_sample": true,
	"max_length": 4096,
	"max_new_tokens": 256,
	"min_length": 0,
	"min_new_tokens": null,
	"early_stopping": false,
	"max_time": null,
	"num_beams": 1,
	"num_beam_groups": 1,
	"diversity_penalty": 0.0,
	"num_return_sequences": 1,
	"output_attentions": false,
	"output_hidden_states": false,
	"output_scores": false,
	"return_dict_in_generate": false,
	"repetition_penalty": 1.0,
	"no_repeat_ngram_size": null,
	"renormalize_logits": false,
	"remove_invalid_values": false,
	"top_k": 40,
	"top_p": 0.9,
	"temperature": 0.3,
	"typical_p": 1.0,
	"epsilon_cutoff": 0.0,
	"eta_cutoff": 0.0,
	"diversity_penalty": 0.0,
	"num_return_sequences": 1,
	"length_penalty": 1.0,
	"bad_words_ids": null,
	"force_words_ids": null,
	"renormalize_logits": false,
	"constraints": null,
	"forced_bos_token_id": null,
	"forced_eos_token_id": null,
	"remove_invalid_values": false,
	"exponential_decay_length_penalty": null,
	"suppress_tokens": null,
	"begin_suppress_tokens": null,
	"forced_decoder_ids": null
	}