Instructions to use QuantFactory/CausalLM-35b-beta-long-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/CausalLM-35b-beta-long-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/CausalLM-35b-beta-long-GGUF",
	filename="CausalLM-35b-beta-long.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use QuantFactory/CausalLM-35b-beta-long-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 QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/CausalLM-35b-beta-long-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 QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/CausalLM-35b-beta-long-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 QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/CausalLM-35b-beta-long-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 QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use QuantFactory/CausalLM-35b-beta-long-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "QuantFactory/CausalLM-35b-beta-long-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "QuantFactory/CausalLM-35b-beta-long-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M

Ollama
How to use QuantFactory/CausalLM-35b-beta-long-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M
```

Unsloth Studio

How to use QuantFactory/CausalLM-35b-beta-long-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 QuantFactory/CausalLM-35b-beta-long-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 QuantFactory/CausalLM-35b-beta-long-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/CausalLM-35b-beta-long-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use QuantFactory/CausalLM-35b-beta-long-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/CausalLM-35b-beta-long-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/CausalLM-35b-beta-long-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.CausalLM-35b-beta-long-GGUF-Q4_K_M

List all available models

lemonade list

Crashes when I try to load it in koboldcpp

by lemon07r - opened May 7, 2024

Discussion

lemon07r

May 7, 2024

Basically the title, same issue with bartowskis quants too. Maybe koboldcpp doesnt have the required upstream merges from llamacpp yet? Wondering if someone can confirm. I tested lost ruins koboldcpp with openblas and vulkan both, and yellowroses hipblas fork, neither can load this model. Tested with Q4k_M

Elfrino

May 7, 2024

Yes, we'll have to wait a bit until KoboldCPP updates this change:

https://github.com/LostRuins/koboldcpp/commit/889bdd76866ea31a7625ec2dcea63ff469f3e981

tastypear

May 8, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Elfrino

May 9, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Hmm. The same error I presume or a different one?

tastypear

May 10, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Hmm. The same error I presume or a different one?

My error is check_tensor_dims: tensor 'token_embd.weight' has wrong shape

🤔Did you load successfully?

Elfrino

May 11, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Hmm. The same error I presume or a different one?

My error is check_tensor_dims: tensor 'token_embd.weight' has wrong shape

🤔Did you load successfully?

I just tried it with the new KoboldCPP just released, works fine :)

https://github.com/LostRuins/koboldcpp/releases

tastypear

May 11, 2024

•

edited May 11, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Hmm. The same error I presume or a different one?

My error is check_tensor_dims: tensor 'token_embd.weight' has wrong shape

🤔Did you load successfully?

I just tried it with the new KoboldCPP just released, works fine :)

https://github.com/LostRuins/koboldcpp/releases

WoW! I know what happens.

GGUFs in bartowski/35b-beta-long-GGUF can be loaded correctly.

GGUFs in this repo will be mistakenly recognized as type llama(should be command-r).

Elfrino

May 12, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Hmm. The same error I presume or a different one?

My error is check_tensor_dims: tensor 'token_embd.weight' has wrong shape

🤔Did you load successfully?

I just tried it with the new KoboldCPP just released, works fine :)

https://github.com/LostRuins/koboldcpp/releases

WoW! I know what happens.

GGUFs in bartowski/35b-beta-long-GGUF can be loaded correctly.

GGUFs in this repo will be mistakenly recognized as type llama(should be command-r).

You mean it works with the new version of KoboldCPP? Or does it work with the older version too?

tastypear

May 12, 2024

@Elfrino I compiled llama.cpp with the latest code. The error persists.

Hmm. The same error I presume or a different one?

My error is check_tensor_dims: tensor 'token_embd.weight' has wrong shape

🤔Did you load successfully?

I just tried it with the new KoboldCPP just released, works fine :)

https://github.com/LostRuins/koboldcpp/releases

WoW! I know what happens.

GGUFs in bartowski/35b-beta-long-GGUF can be loaded correctly.

GGUFs in this repo will be mistakenly recognized as type llama(should be command-r).

You mean it works with the new version of KoboldCPP? Or does it work with the older version too?

Only new version of KoboldCPP & llama.cpp work. They support the command-r type which Causallm-35B is based on.

This repo is deprecated as the model should be quantized again. bartowski/35b-beta-long-GGUF is correct.

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