Instructions to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf", filename="Prima-LelantaclesV7-experimental-7b.IQ3_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
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 RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
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 RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
Use Docker
docker model run hf.co/RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf with Ollama:
ollama run hf.co/RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
- Unsloth Studio
How to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf 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 RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf 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 RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf to start chatting
- Atomic Chat new
- Docker Model Runner
How to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf with Docker Model Runner:
docker model run hf.co/RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
- Lemonade
How to use RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RichardErkhov/ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf:Q4_K_M
Run and chat with the model
lemonade run user.ChaoticNeutrals_-_Prima-LelantaclesV7-experimental-7b-gguf-Q4_K_M
List all available models
lemonade list
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Quantization made by Richard Erkhov.
Prima-LelantaclesV7-experimental-7b - GGUF
- Model creator: https://huggingface.co/ChaoticNeutrals/
- Original model: https://huggingface.co/ChaoticNeutrals/Prima-LelantaclesV7-experimental-7b/
Original model description:
license: other library_name: transformers tags: - mergekit - merge base_model: - Nitral-AI/Prima-LelantaclesV6.69-7b - Nitral-AI/Prima-LelantaclesV6.31-7b model-index: - name: Prima-LelantaclesV7-7b results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 70.65 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Prima-LelantaclesV7-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 87.94 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Prima-LelantaclesV7-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.67 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Prima-LelantaclesV7-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 67.45 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Prima-LelantaclesV7-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 84.69 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Prima-LelantaclesV7-7b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 62.77 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/Prima-LelantaclesV7-7b name: Open LLM Leaderboard
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: Nitral-AI/Prima-LelantaclesV6.69-7b
layer_range: [0, 32]
- model: Nitral-AI/Prima-LelantaclesV6.31-7b
layer_range: [0, 32]
merge_method: slerp
base_model: Nitral-AI/Prima-LelantaclesV6.69-7b
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 73.03 |
| AI2 Reasoning Challenge (25-Shot) | 70.65 |
| HellaSwag (10-Shot) | 87.94 |
| MMLU (5-Shot) | 64.67 |
| TruthfulQA (0-shot) | 67.45 |
| Winogrande (5-shot) | 84.69 |
| GSM8k (5-shot) | 62.77 |
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