Instructions to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf with Transformers:

# Use a pipeline as a high-level helper
# Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline

pipe = pipeline("image-to-text", model="chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf", dtype="auto")

llama-cpp-python

How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf",
	filename="EraX-VL-7B-V1.5.IQ4_XS.gguf",
)

llm.create_chat_completion(
	messages = "\"cats.jpg\""
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.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 chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.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 chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.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 chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.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 chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M

Use Docker

docker model run hf.co/chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf with Ollama:
```
ollama run hf.co/chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M
```

Unsloth Studio

How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.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 chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.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 chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf to start chatting

Atomic Chat new
Docker Model Runner
How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf with Docker Model Runner:
```
docker model run hf.co/chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M
```

Lemonade

How to use chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull chiakelvin/EraX-VL-7B-V1.5.Q5_K_M.gguf:Q4_K_M

Run and chat with the model

lemonade run user.EraX-VL-7B-V1.5.Q5_K_M.gguf-Q4_K_M

List all available models

lemonade list

chiakelvin

mradermacher commited on about 7 hours ago

Commit

995d5f2

0 Parent(s):

Duplicate from mradermacher/EraX-VL-7B-V1.5-GGUF

Browse files

Co-authored-by: team mradermacher <mradermacher@users.noreply.huggingface.co>

Files changed (15) hide show

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+---
+base_model: erax-ai/EraX-VL-7B-V1.5
+language:
+- vi
+- en
+- zh
+library_name: transformers
+license: apache-2.0
+quantized_by: mradermacher
+tags:
+- erax
+- multimodal
+- erax-vl-7B
+- insurance
+- ocr
+- vietnamese
+- bcg
+- image-to-text
+---
+## About
+<!-- ### quantize_version: 2 -->
+<!-- ### output_tensor_quantised: 1 -->
+<!-- ### convert_type: hf -->
+<!-- ### vocab_type:  -->
+<!-- ### tags: nicoboss -->
+static quants of https://huggingface.co/erax-ai/EraX-VL-7B-V1.5
+<!-- provided-files -->
+weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
+## Usage
+If you are unsure how to use GGUF files, refer to one of [TheBloke's
+READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
+more details, including on how to concatenate multi-part files.
+## Provided Quants
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.mmproj-fp16.gguf) | mmproj-fp16 | 1.5 | multi-modal supplement |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q2_K.gguf) | Q2_K | 3.1 |  |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q3_K_S.gguf) | Q3_K_S | 3.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q3_K_L.gguf) | Q3_K_L | 4.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.IQ4_XS.gguf) | IQ4_XS | 4.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q5_K_S.gguf) | Q5_K_S | 5.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q5_K_M.gguf) | Q5_K_M | 5.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/EraX-VL-7B-V1.5-GGUF/resolve/main/EraX-VL-7B-V1.5.f16.gguf) | f16 | 15.3 | 16 bpw, overkill |
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
+And here are Artefact2's thoughts on the matter:
+https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+## FAQ / Model Request
+See https://huggingface.co/mradermacher/model_requests for some answers to
+questions you might have and/or if you want some other model quantized.
+## Thanks
+I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
+<!-- end -->