Instructions to use LogicismTV/Toppy-M-7B-exl2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LogicismTV/Toppy-M-7B-exl2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="LogicismTV/Toppy-M-7B-exl2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LogicismTV/Toppy-M-7B-exl2")
model = AutoModelForCausalLM.from_pretrained("LogicismTV/Toppy-M-7B-exl2")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use LogicismTV/Toppy-M-7B-exl2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LogicismTV/Toppy-M-7B-exl2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LogicismTV/Toppy-M-7B-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LogicismTV/Toppy-M-7B-exl2

SGLang

How to use LogicismTV/Toppy-M-7B-exl2 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 "LogicismTV/Toppy-M-7B-exl2" \
    --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": "LogicismTV/Toppy-M-7B-exl2",
		"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 "LogicismTV/Toppy-M-7B-exl2" \
        --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": "LogicismTV/Toppy-M-7B-exl2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LogicismTV/Toppy-M-7B-exl2 with Docker Model Runner:
```
docker model run hf.co/LogicismTV/Toppy-M-7B-exl2
```

Vist my Website

Join my Discord

Toppy M 7B - ExLlama V2

Original model: Toppy M 7B

Description

This is an EXL2 quantization of the Undi95's Toppy M 7B model.

Prompt template: Alpaca

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

Quantizations

Bits Per Weight	Size
main (2.4bpw)	2.29 GB
3bpw	2.78 GB
3.5bpw	3.19 GB
4bpw	3.59 GB
4.5bpw	4.00 GB
5bpw	4.41 GB
6bpw	5.22 GB
8bpw	6.84 GB

Original model card: Carsten Kragelund's Chronomaid Storytelling 13B

Description

This repo contains fp16 files of Toppy-M-7B, a merge I have done with the new task_arithmetic merge method from mergekit.

This project was a request from BlueNipples : link

Models and loras used

The sauce

openchat/openchat_3.5
lemonilia/AshhLimaRP-Mistral-7B (LoRA) x 0.38

NousResearch/Nous-Capybara-7B-V1.9
Vulkane/120-Days-of-Sodom-LoRA-Mistral-7b x 0.27

HuggingFaceH4/zephyr-7b-beta
Undi95/Mistral-pippa-sharegpt-7b-qlora x 0.38

merge_method: task_arithmetic
base_model: mistralai/Mistral-7B-v0.1
models:
  - model: mistralai/Mistral-7B-v0.1
  - model: Undi95/zephyr-7b-beta-pippa-sharegpt
    parameters:
      weight: 0.42
  - model: Undi95/Nous-Capybara-7B-V1.9-120-Days
    parameters:
      weight: 0.29
  - model: Undi95/openchat_3.5-LimaRP-13B
    parameters:
      weight: 0.48
dtype: bfloat16

Prompt template: Alpaca

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

If you want to support me, you can here.

Downloads last month: 5

Model tree for LogicismTV/Toppy-M-7B-exl2

Base model

Undi95/Toppy-M-7B

Finetuned

(2)

this model