Instructions to use RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use RichardErkhov/interview-eval_-_zephyr-7b-math-test-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/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/interview-eval_-_zephyr-7b-math-test-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/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M # Run inference directly in the terminal: llama cli -hf RichardErkhov/interview-eval_-_zephyr-7b-math-test-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/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf RichardErkhov/interview-eval_-_zephyr-7b-math-test-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/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M
Use Docker
docker model run hf.co/RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf with Ollama:
ollama run hf.co/RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf with Docker Model Runner:
docker model run hf.co/RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M
- Lemonade
How to use RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull RichardErkhov/interview-eval_-_zephyr-7b-math-test-gguf:Q4_K_M
Run and chat with the model
lemonade run user.interview-eval_-_zephyr-7b-math-test-gguf-Q4_K_M
List all available models
lemonade list
- Atomic Chat
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Quantization made by Richard Erkhov.
zephyr-7b-math-test - GGUF
- Model creator: https://huggingface.co/interview-eval/
- Original model: https://huggingface.co/interview-eval/zephyr-7b-math-test/
| Name | Quant method | Size |
|---|---|---|
| zephyr-7b-math-test.Q2_K.gguf | Q2_K | 2.53GB |
| zephyr-7b-math-test.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| zephyr-7b-math-test.IQ3_S.gguf | IQ3_S | 2.96GB |
| zephyr-7b-math-test.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| zephyr-7b-math-test.IQ3_M.gguf | IQ3_M | 3.06GB |
| zephyr-7b-math-test.Q3_K.gguf | Q3_K | 3.28GB |
| zephyr-7b-math-test.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| zephyr-7b-math-test.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| zephyr-7b-math-test.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| zephyr-7b-math-test.Q4_0.gguf | Q4_0 | 3.83GB |
| zephyr-7b-math-test.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| zephyr-7b-math-test.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| zephyr-7b-math-test.Q4_K.gguf | Q4_K | 4.07GB |
| zephyr-7b-math-test.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| zephyr-7b-math-test.Q4_1.gguf | Q4_1 | 4.24GB |
| zephyr-7b-math-test.Q5_0.gguf | Q5_0 | 4.65GB |
| zephyr-7b-math-test.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| zephyr-7b-math-test.Q5_K.gguf | Q5_K | 4.78GB |
| zephyr-7b-math-test.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| zephyr-7b-math-test.Q5_1.gguf | Q5_1 | 5.07GB |
| zephyr-7b-math-test.Q6_K.gguf | Q6_K | 5.53GB |
| zephyr-7b-math-test.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
library_name: transformers license: apache-2.0 base_model: alignment-handbook/zephyr-7b-sft-full tags: - alignment-handbook - trl - sft - generated_from_trainer - trl - sft - generated_from_trainer datasets: - EunsuKim/MATH model-index: - name: zephyr-7b-math-test results: []
zephyr-7b-math-test
This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the EunsuKim/MATH dataset. It achieves the following results on the evaluation set:
- Loss: 0.0178
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8684 | 1.0 | 5 | 0.7914 |
| 0.7031 | 2.0 | 10 | 0.5349 |
| 0.4888 | 3.0 | 15 | 0.3412 |
| 0.302 | 4.0 | 20 | 0.1902 |
| 0.1643 | 5.0 | 25 | 0.0890 |
| 0.0778 | 6.0 | 30 | 0.0416 |
| 0.0404 | 7.0 | 35 | 0.0280 |
| 0.0279 | 8.0 | 40 | 0.0219 |
| 0.0214 | 9.0 | 45 | 0.0186 |
| 0.0183 | 10.0 | 50 | 0.0178 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1
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