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PR_kwDOJ0Z1Ps5thxhS
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Update windows.md
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Fixed a typo
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PR_kwDOJ0Z1Ps5zOINU
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fix: quantization with template
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I_kwDOJ0Z1Ps57_Z4R
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Will ollama run dolphin-mixtral on my gtx 1080 Ti?
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Im just asking since im about to buy one and im curious if it will see the gpu and use it to generate responses faster? Or does Ollama support all Nvidia gpus?
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I_kwDOJ0Z1Ps6Tk_Ds
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Update model parameters for SmolLM (and other models)
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### What is the issue?
It is crucial to follow the recommended model parameters, especially for such small models such as SmolLM. They are much worse at higher temperatures. Ollama team, respectfully, PLEASE make sure the model parameters are set correctly 🙏
From the SmolLM HF:
### OS
_No response_
### GPU
_No response_
### CPU
_No response_
### Ollama version
_No response_
|
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PR_kwDOJ0Z1Ps51TsEO
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add chat and generate tests with mock runner
|
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PR_kwDOJ0Z1Ps6GAaQz
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api: enable passing images in `raw` mode
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I belive this should be considered a bug fix, as it resolves unexpected behavior and clarifies how to use undocumented capabilities - Images were not being passed to multimodal models when `images` were provided and `raw` was set to true as described in [this issue](https://github.com/ollama/ollama-python/issues/319).
This change introduces an optional boolean parameter `prepend_images_to_raw_prompt`, which if set to `true` will add the image placeholder fields necessary to pass the images through to the multimodal model. This parameter only has effect if `raw` is also set to true and `images` are provided. The `prepend_images_to_raw_prompt` parameter can be omitted, and the default behavior remains entirely unchanged to avoid breaking existing users.
It also updates the api.md documentation to describe the new functionality (including an example request/response), and also provides and example of manually passing an image placeholder in the text of a raw prompt directly, which offers more control over where the image is inserted in the raw prompt.
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Ollama's API Confusion
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I started two ports in my server as ollama's api service ports, 8080 and 8081, 8080 as my LLM-api, 8081 as my Embedding-api, but when I add a model to 8080, I can actually see the model on port 8080 by using the following command, but the following command It should see the model for port 8081:
curl http://192.168.18.165:8081/api/tags
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`ollama run` fails on start
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```
➜ ~ ollama run llama2
⠋ Error: template: :2:11: executing "" at <.Context>: can't evaluate field Context in type struct { First bool; System string; Prompt string }
➜ ~ ollama --version
ollama version 0.1.13
```
Ran into this issue after running `ollama run llama2`. Occurs if server is running or if not & issue persisted after updating the server.
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PR_kwDOJ0Z1Ps5tRFfO
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docs: added Ollama Operator into README.md as one of community projects
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First of all, huge thank you to all the wonderful work and awesome contributors to you folks for both ollama, llama.cpp and researchers worked on it.
It made it easy for us to deploy and host our own large language model.
## Summary
I'm Neko Ayaka (https://github.com/nekomeowww) from China.
I'm currently working as a full-stack senior developer at @DaoCloud, diving deep into cloud native tech, AI, and UI/UX design.
Ollama is decent to deploy as single instance on machines like Macbook, Mac Studio. I'm really pumped about how we designed the ollama cli. It keeps things simple for users, much like what Docker does (it reminds me Docker CLI every time I use it). And the implementation of `Modelfile` in the project really streamlines the process, again reminds me `Dockerfile`.
Additionally, I researched the users needs, and interested in over the official Discord server of Ollama, found that many users are researching to find a way to deploy it concurrently.
Therefore, inspired by the awesome user experience with ollama, I wanted to bring that same vibe to my own Kubernetes setup at home. That's where the idea for this project started, fueled by conversations with friends who are also into cloud native projects.
This is the open-source project called Ollama Operator (GitHub: https://github.com/nekomeowww/ollama-operator, documentation site: https://ollama-operator.ayaka.io/pages/en/ ) I want to introduce and add to README of Ollama here.
It's built around a Kubernetes operator concept by leveraging both `ollama pull` and `ollama serve` to make it possible to deploy multiple instances of `ollama serve` to inference multiple models across nodes of clusters by introducing [`Model` CRD](https://ollama-operator.ayaka.io/pages/en/references/crd/model.html), like this:
```yaml
apiVersion: ollama.ayaka.io/v1
kind: Model
metadata:
name: phi
spec:
# Scale the model to 2 replicas
replicas: 2
# Use the model image `phi`
image: phi
```
I've mapped out the specs and CRDs for deploying ollama instances on Kubernetes. There are still a few kinks to iron out, but it's looking good as a proof of concept. I've put together all the docs, the architectural design, and even got it up on a neat documentation site powered by VitePress!
Besides Ollama Operator, and the introduced `Model` CRD to simplify the process of multi-instance deployment, I've also made a CLI tool called `kollama` (source at: https://github.com/nekomeowww/ollama-operator/tree/main/cmd/kollama , documentation site: https://ollama-operator.ayaka.io/pages/en/references/cli/commands/deploy.html ) to even simplify the interactions with introduced `Model` CRD with just a single command, like this:
```shell
kollama deploy phi --expose
```
I have Ollama Operator running on our team's dedicated server, my own development `kind` cluster on my Macbook, and the general K8s cluster on my Homelab, little testing k3s cluster on my two Respberry Pi. They are running smoothly for fine for the past 10 days, and I consider it is a general available project for users to try out and feedback to me to improve the project continously.
> There are still much work to do and many things worth me to research and test, I really want to share the concepts, design, simplified concepts with Kubernets.
## Proposal
Add and include [Ollama Operator](https://github.com/nekomeowww/ollama-operator) into Ollama's `README.md` file as one of the community driven project.
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I_kwDOJ0Z1Ps6gPWbe
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Multiple prompt support over stdin.
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edit: Important clarifications on a misunderstanding from me on the current implementation at https://github.com/ollama/ollama/issues/7823#issuecomment-2542541753
These points still stay relevant, but might be easier to understand by reading the comment first.
In [pull 416](https://github.com/ollama/ollama/pull/416), the ability to enter multiple prompts over STDIN directly seems to have been removed.
To work around this, I recently made an `except` script (assembler in Fish) which filters out the interface related outputs elements of `ollama run`.
In version 0.4.3, this achieves the desired effect of only outputting model output through the pipe, while allowing for multiple prompts.
I will share my script in the first comment.
As I mentioned in [issue 7820](https://github.com/ollama/ollama/issues/7820), this method of inputting has been broken as per version 0.4.4.
And as mentioned by @rick-github in [their comment](https://github.com/ollama/ollama/issues/7820#issuecomment-2496152849), this likely is by design, due to [pull 7360](https://github.com/ollama/ollama/pull/7360).
Which at face value seems to completely cover my use-case and avoids the jank of a script parsing the interface information.
But the current implementation breaks entering prompts manually or through `expect` (my [issue 7820](https://github.com/ollama/ollama/issues/7820) again), while piping the output to `tee` or similar.
I will explore the proposed `script` based workaround [mentioned by @rick-github](https://github.com/ollama/ollama/issues/7820#issuecomment-2496152849), either adding it to or replacing my `expect` based workaround with it.
Like my script, this still is an excessive level of workarounds to make something which would be expected functionality work.
**Potential solutions:**
- Not having `ollama run` immediately close with output redirection, as the implementation from [pull 7360](https://github.com/ollama/ollama/pull/7360) does.
- Having some form of delimiter within the """ syntax, for starting a new prompt, like:
```
"""
First prompt.
---
Second prompt.
"""
```
This could start processing the first/earlier prompt after the --- delimiter is received to allow for full dialogue
- Some feature flag to interpret STDIN as user input, similar to [pull 6130](https://github.com/ollama/ollama/pull/6130) (which [pull 7360](https://github.com/ollama/ollama/pull/7360) replaced).
Perhaps `--input user`, `--nogui`, `--keeppipe`, ect.
- Having multiple prompts passed as arguments processed sequentially, like the shared script does.
Of course, this is only a feature *request*, it's fine if piping multiple prompts over STDIN or as arguments is not supported.
In which case I would be fine with looking further and interested in suggestions for other frontends or libraries to use.
P.S. Since making such a feature request is a first for me, constructive criticism is welcome if you can spare the time.
Either way, have a nice rest of your day!
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PR_kwDOJ0Z1Ps5jRorQ
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|
fix docker doc to point to hub
|
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there is a link that should point to dockerhub which is the best place to understand docker
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Ministral-8B-Instruct-2410
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https://huggingface.co/mistralai/Ministral-8B-Instruct-2410
<img width="1633" alt="instruct_table_with_gemma" src="https://github.com/user-attachments/assets/23eb1742-ee5e-475a-bf7b-5853f781c4f7">
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I_kwDOJ0Z1Ps6choUD
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Error: unknown error was encountered while running the model GGML_ASSERT(i01 >= 0 && i01 < ne01) failed
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### What is the issue?
[Nanollava](https://ollama.com/qnguyen3/nanollava) returns `GGML_ASSERT(i01 >= 0 && i01 < ne01) failed` error on chat with image
Output:
```bash
ubuntu@ubuntu:~/workspace$ ollama run qnguyen3/nanollava "tell me what do you see in this picture? ./sample.jpg"
Added image './sample.jpg'
Error: an unknown error was encountered while running the model GGML_ASSERT(i01 >= 0 && i01 < ne01) failed
```
### OS
Linux
### GPU
Other
### CPU
AMD
### Ollama version
0.3.14
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PR_kwDOJ0Z1Ps5ua2-7
| 4,109
|
Add information on model tagging to `import.md`.
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I added a section to the import documentation on model tagging and cleaned up the quantization reference section a smidge.
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PR_kwDOJ0Z1Ps5ySn5l
| 5,009
|
move OLLAMA_HOST to envconfig
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Add Community Integration: OllamaGUI
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👋 I have added new integrations for macos!
https://github.com/ollama/ollama/assets/54224095/eff7fd87-d8f6-4b97-bf06-f52e40e56dcc
link: https://github.com/enoch1118/ollamaGUI
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I_kwDOJ0Z1Ps6VOWQp
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GPU Not Use
|
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NONE
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Hello, I am using Windows 11 and I have installed LLama3.1 7B and Gemma 2 27B in Ollama. When using these modems the GPU is between 0%-1%. What should I do?
My laptop specs are:
HP Victus
14700hx
4070
32 GB Ram
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I_kwDOJ0Z1Ps585SQw
| 2,154
|
How to design our own prompt by import ollama?
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| 2024-01-23T07:04:42
| 2024-03-12T22:54:26
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|
NONE
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假如我想设计一个CR相关的prompt(比如：你是一个CR专家，请帮我根据提供的代码判断是否符标准...),并且通过 import ollama的python方法去调用大模型，我应该如何操作？
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I_kwDOJ0Z1Ps6PDPIQ
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Ollama running requests slow, while not utilizing entire VRAM
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| 2024-07-10T07:35:29
| 2024-07-26T18:17:53
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NONE
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I am continuously sending "generate" API requests to the Ollama server, querying the model wizardlm2:7b-q6_K. Each iteration takes approximately 3 seconds to respond. The model is using only 8GB of the 16GB VRAM available on my Tesla V100 GPU.
Is there a way to make it utilize the entire VRAM to speed up request processing? If so, how can I achieve this?
|
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doc: Add reference to package managers in Linux Installation section
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CONTRIBUTOR
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Unexpected Increase in Inference Time as Context Window Grows on Llama3:7b
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### What is the issue?
I am doing some benchmarks on RAG using llama3:7b model on Ollama.
I ask a question first directly to the model, then ask the question and provide context from relevant documents, asking the model to answer the question based on the given context; essentially, asking the question in the RAG way without exceeding the model's context window. As expected, the first query is a sentence long, and the second query is many sentences long.
I asked 14 questions (14 queries for direct questions and 14 queries for RAG questions in total for each machine) and the benchmark results can be seen below:
| Machine Type | CPU | RAM (GB) | Graphics Card | OS | Direct Question - Short Context (ms) | RAG Question - Long Context (ms) |
|----------------|----------------------------------------|----------|--------------------------------------------------|------------------|------------|----------|
| Mac Mini | Apple Silicon M2 Pro | 16 | | macOS 14.2.1 | 61152 | 105998 |
| Laptop | AMD Ryzen 9 5900HX (16) @ 4.680GHz | 32 | NVIDIA GeForce RTX 3050 Mobile, AMD ATI Cezanne | Pop!_OS 22.04 LTS| 413264 | 1052304 |
| Desktop | 11th Gen Intel i5-11400F (12) @ 4.400GHz| 64 | NVIDIA GeForce RTX 3060 Lite Hash Rate | Pop!_OS 22.04 LTS| 114599 | 152341 |
I use Ollama version 0.1.34. As far as I know, inference time doesn't change significantly as query context grows for LLMs. I am particularly surprised to see more than a 2.5x increase in inference time on my laptop machine. I haven't performed this benchmark on a different model than Llama3.
I wonder if something is wrong with Ollama or if these benchmark results I am getting are normal.
Thanks!
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.1.34
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I_kwDOJ0Z1Ps6k0R92
| 8,281
|
Runing ollama on Intel Ultra NPU or GPU
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NONE
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After I installed ollama through ollamaSetup, I found that it cannot use my gpu or npu. How to solve this problem?
CPU: intel ultra7 258v
System: windows 11 24h2
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PR_kwDOJ0Z1Ps5U9BQy
| 57
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take all args as one prompt
|
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- parse all run arguments into one prompt
- do not echo prompt back on one-shot
- example of summarizing a document
```
$ ollama run nous-hermes "$(cat input.txt)", please summarize this story
The song "Summertime" by Will Smith is about the rapper's life before fame and how it changed when he became successful. The lyrics describe his experiences growing up in Philadelphia and then suddenly becoming rich and famous. The song is a coming-of-age story that describes the rapper's journey from poverty to stardom, and the impact of this change on his life.
```
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bump
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Add Laravel package to README.md
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I_kwDOJ0Z1Ps6iuNk8
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OpenAI Chat Completion Client For Multimodal
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| 2024-12-10T12:42:53
| 2024-12-26T05:02:37
| 2024-12-26T05:02:37
|
NONE
|
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Inconsistency with openai standard api parameters
```python
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is in this image?",
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{base64_image}"
},
},
],
}
],
)
```
|
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|
I_kwDOJ0Z1Ps6jwmEV
| 8,154
|
I can not connect to 11434 port
|
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| null |
[] | null | 1
| 2024-12-18T10:30:19
| 2024-12-19T19:56:10
| null |
NONE
|
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| null | null | null |
### What is the issue?
sir, i add Environment="OLLAMA_HOST=0.0.0.0" to the service file,Then i restart ollama. now, i find the service listener port is only have tcp6，without tcp4 listen，so i can not access to the service from other machine. how can i fix this problem？ thank you
[root@localhost ollama]# netstat -tuln | grep 11434
tcp6 0 0 :::11434 :::* LISTEN
[root@localhost ollama]#
### OS
_No response_
### GPU
_No response_
### CPU
_No response_
### Ollama version
_No response_
| null |
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| 2,266,528,424
|
PR_kwDOJ0Z1Ps5t4gfb
| 3,960
|
server: add dynamic configuration for download variables
|
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[] | null | 3
| 2024-04-26T21:27:46
| 2024-11-21T14:47:44
| 2024-11-21T09:56:35
|
NONE
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|
## Issue
I've found that downloads can be unreliable for large models, either due to errors during the download or during processing the digest.
## Workaround
Add some environment variables to the server to allow runtime configuration of the number of parallel downloads and how big the chunks can be.
## Follow-up
Ideally the server would be configured to respect the `?partNumber` query parameters that the returned `x-amz-mp-parts-count` header implies should be supported. I'd also like it to support `x-amz-checksum-mode=ENABLED` (currently returns a `501 NOT IMPLEMENTED`), so that each part number returns an expected digest in the response headers for `GET` and `HEAD`. This would enable us to split the digest by parts, so that if a part download fails, we don't need to retrieve the full model each time.
It seems that the current implementation is done via [github.com/distribution/distribution](github.com/distribution/distribution), which delegates its `Range` handling to `http.ServeContent`, and as such does not support the `partNumber` functionality implied by the CloudFlare response headers. So any such support would have to fork github.com/distribution/distribution. CloudFlare also does not appear to support these headers.
|
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I_kwDOJ0Z1Ps6iabsh
| 7,990
|
Incorrect version for v0.5.1 - ollama version is 0.4.4
|
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| 2024-12-07T22:27:56
| 2024-12-07T22:28:57
| 2024-12-07T22:28:57
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NONE
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### What is the issue?
`ollama` binary from ollama-linux-amd64.tgz from https://github.com/ollama/ollama/releases/tag/v0.5.1 shows incorrect version 0.4.4.
```
$ bin/ollama --version
ollama version is 0.4.4
Warning: client version is 0.5.1
```
### OS
Linux
### GPU
Intel
### CPU
Intel
### Ollama version
v0.5.1
|
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PR_kwDOJ0Z1Ps5u0XnE
| 4,241
|
Detect noexec and report a better error
|
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| 2024-05-07T23:49:02
| 2024-05-08T22:34:25
| 2024-05-08T22:34:22
|
COLLABORATOR
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This will bubble up a much more informative error message if noexec is preventing us from running the subprocess
Fixes #4105
Repro scenario:
```
sudo mkdir /tmp2
sudo mount -t tmpfs -o size=1g,noexec tmpfs /tmp2
OLLAMA_TMPDIR=/tmp2/test1 ollama serve
...
time=2024-05-07T23:44:54.304Z level=INFO source=sched.go:308 msg="NewLlamaServer failed" model=/home/daniel/.ollama/models/blobs/sha256-66002b78c70a22ab25e16cc9a1736c6cc6335398c7312e3eb33db202350afe66 error="unable to start server fork/exec /tmp2/test1/runners/cpu_avx/ollama_llama_server: permission denied. /tmp2/test1/runners/cpu_avx may have noexec set. Set OLLAMA_TMPDIR for server to a writable executable directory"
```
On the client that triggered the failure:
```
% ollama run orca-mini hello
Error: unable to start server fork/exec /tmp2/test1/runners/cpu_avx/ollama_llama_server: permission denied. /tmp2/test1/runners/cpu_avx may have noexec set. Set OLLAMA_TMPDIR for server to a writable executable directory
```
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PR_kwDOJ0Z1Ps5f1L1O
| 1,195
|
progress: fix bar rate
|
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[] | null | 3
| 2023-11-19T02:37:58
| 2023-11-28T19:55:24
| 2023-11-28T19:55:23
|
CONTRIBUTOR
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implement rate as a rolling average over the last n updates.
the current issue is rate is calculated as an average rate over the lifetime of the progress bar. this reflects the actual progress well if the progress is smooth and flat but that's rarely the case.
the rolling average is a better way to represent changing rates. if more progress is made in the window than before, the rate will go up. if less progress is made, the rate will go down
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I_kwDOJ0Z1Ps6Qea7s
| 5,863
|
function calling documentation
|
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While searching the web I couldn't yet find a resource except function callilng through mistral_inference package.
I am curious whether anyone wrote a raw prompt in which function calling is working?
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Nvidia Minitron Please!
|
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| 2024-09-10T17:12:18
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NONE
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https://huggingface.co/collections/nvidia/minitron-669ac727dc9c86e6ab7f0f3e
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I_kwDOJ0Z1Ps6IlhtD
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Ollama "ollama show --modelfile" shows license instead of modelfile
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| 2024-05-12T23:02:26
| 2024-05-14T09:35:14
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NONE
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### What is the issue?
When the command 'ollama show --modelfile llama3:70b' is entered, it should have displayed information about the model's modelfile, but instead, it displayed license information.
The "--modelfile: parameter for "ollama show" command seems not working.
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.1.36
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I_kwDOJ0Z1Ps5vIOZr
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Ollama Windows version
|
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| 2023-08-24T05:23:02
| 2024-05-23T11:31:34
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I saw it is coming but didn't mention when? Would be great if you pinned this issue as more people use Windows & ollama has such a great dx.
The project looks absolutely brilliant. Would love to use text (gpt-4) & code (copilot) locally.
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Whether Qwen from ollama library is Qwen1.5?
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| 2024-04-04T11:19:33
| 2024-04-23T23:20:56
| 2024-04-17T22:02:09
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### What model would you like?
When I type ollama run qwen:7b and the command completed successfully, but may I know whether the Qwen is Qwen or Qwen1.5, because I saw Qwen1.5 in Github.
If not, please add Qwen1.5 to ollama library.
Thanks,
|
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I_kwDOJ0Z1Ps6XjNn_
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|
downloadChunk does not pass the Authorization header to the registry
|
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| 2024-10-05T21:54:04
| null |
CONTRIBUTOR
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### What is the issue?
In #5994 , `regOpts` were removed from the `blobDownload.downloadChunk` method as unnecessary. While it's true that the ollama library only offers public blobs, the lack of regOpts means that all `GET /v2/<image>/blobs/...` requests with a `Range` header cannot be accompanied by an `Authorization` header.
This removal now breaks the mirrored behavior with [blobUpload.uploadPart](https://github.com/ollama/ollama/blob/main/server/upload.go#L152) where the RegOpts and corresponding `Authorization header` are still passed to each invocation.
I tried adding the `Authorization: Bearer` token to the request, but it looks like pulls from `registry.ollama.ai` are breaking with this change, most likely because the header is being passed to the cloudflarestorage.com URLs.
```
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
0.3.11
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PR_kwDOJ0Z1Ps6JYzfR
| 8,668
|
Hide empty terminal window
|
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This hides the LlamaServer blank window when chatting outside of the terminal (say like with an app like Msty). This has no other side effects when invoking it the regular way.
I had sent a PR for this a while ago and it was closed thinking it had been resolved but this issue still exists. (see: https://github.com/ollama/ollama/pull/4287)
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I_kwDOJ0Z1Ps6GJZ7F
| 3,732
|
num_gpu is not working in modelfile based on another model.
|
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| 2024-04-18T12:48:15
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### What is the issue?
First I downloaded wizardlm2:8x22b.
`ollama pull wizardlm2:8x22b`
I'm trying to offload only 30 layers to gpu using this modelfile with PARAMETER num_gpu 30:
```
FROM wizardlm2:8x22b
TEMPLATE """{{ if .System }}{{ .System }} {{ end }}{{ if .Prompt }}USER: {{ .Prompt }} {{ end }}ASSISTANT: {{ .Response }}"""
SYSTEM """A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions."""
PARAMETER stop "USER:"
PARAMETER stop "ASSISTANT:"
PARAMETER num_gpu 30
```
However, server.log indicates 0 layers are offloaded.
If I create a model from .gguf file that I downloaded from HF, it works.
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
0.3.2
|
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PR_kwDOJ0Z1Ps5vCazn
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|
Fix race in shutdown logic
|
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| 2024-05-09T22:48:49
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Ensure the runners are terminated
Fixes #4267
|
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|
Add isolated gpu test to troubleshooting
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This should help users isolate problems with their container runtime.
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Unable to enable GPU for models
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### What is the issue?
I don't have much knowledge in this kind of stuff, so I followed the instructions and installed ollama. But when I run the model, only CPU is working and my nvidia GPU doesn't work at all. I am wondering how can I enable GPU for ollama. Thanks a lot.
### OS
Windows
### GPU
Nvidia
### CPU
Intel
### Ollama version
0.5.4
|
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Could not install deepseek-r1:7b version
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| 2025-01-29T09:42:18
| 2025-01-30T08:54:15
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### What is the issue?
Error: max retries exceeded: Get "https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/aa/aabd4debf0c8f08881923f2c25fc0fdeed24435271c2b3e92c4af36704040dbc/data?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=66040c77ac1b787c3af820529859349a%2F20250129%2Fauto%2Fs3%2Faws4_request&X-Amz-Date=20250129T093708Z&X-Amz-Expires=86400&X-Amz-SignedHeaders=host&X-Amz-Signature=044eb3053c34ac7e27101080923c27a8d4f0adc5334de93463391b2cf3d208cd": dial tcp: lookup dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com: no such host
### OS
Windows
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.5.7
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PR_kwDOJ0Z1Ps5cId8b
| 720
|
relay model runner error message to client
|
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This got missed in the migration to subprocesses.
Old error displayed in CLI:
```
failed to start llama runner
```
New error (will relay the actual error from the model runner):
```
Error: llama runner failed: out of memory
```
resolves #630
|
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Added ollama4j-web-ui to the list of community developed user interfaces
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fix show handler
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the show handler is unique in the sense that the request struct is passed directly to `GetModel` while every other handler deconstructs the request into its parameters. therefore the pattern of setting a local variable `model` and setting it to req.Model or req.Name doesn't work
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PR_kwDOJ0Z1Ps5vItCX
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|
Integration fixes
|
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I_kwDOJ0Z1Ps6HUlwT
| 4,038
|
ollama run codeqwen TLS handshake timeout
|
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NONE
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### What is the issue?
After I manually installed ollama locally, I started to try to run models, not only qianwne, but also llama3. But ping ollama.com does work. Since I am building ollama on the server, I was wondering if it would be possible to download the model file locally and drag it to the specified path on the server. If you can do this, could you give me some help? I don't know what path the pulled model should be placed under, thank you.
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.1.32
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I_kwDOJ0Z1Ps5_g3_L
| 2,550
|
WIndows questions sorry
|
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NONE
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How do you login using windows since theres no cat funciton
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I_kwDOJ0Z1Ps59VYFk
| 2,213
|
Interleaving text and images (for few-shot learning)
|
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| 2024-01-26T19:13:36
| 2024-09-04T18:31:10
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It does not appear to be possible (e.g. with llava) to interleave images and text (or is it?).
This would be necessary in order to give some few-shot examples of image-text pairs, and then a final image that we want to generate text for. For example, the [OpenAI API](https://platform.openai.com/docs/guides/vision) allows for this by having the `content` field be a list, where each entry can be either text, or a base64-encoded image. (The examples in their docs do not show it, but it is indeed possible to interleave images and text arbitrarily using that API.)
I am not sure this is possible with the underlying llava model (or others), but if it is, it would be a great feature to have.
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I_kwDOJ0Z1Ps6BhkK-
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How to run Windows version Ollama on AMD GPU?
|
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I have a W6800, apparently windows version Ollama is running models on CPU rather than GPU. Will AMD GPU be supported?
|
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Update troubleshooting.md with troubleshooting details for containers.
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Update troubleshooting.md with troubleshooting details for containers.
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I_kwDOJ0Z1Ps6Xaz1s
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nexusraven:13b-v2-q2_K EOF
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### What is the issue?
either using the API or the CLI, I can't get nexusraven:13b-v2-q2_K to work (other models work fine)
```
ollama pull nexusraven:13b-v2-q2_K
OLLAMA_DEBUG="1" ollama run nexusraven:13b-v2-q2_K
Error: Post "http://127.0.0.1:11434/api/generate": EOF
```
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.3.11
|
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I_kwDOJ0Z1Ps5-n2OS
| 2,406
|
systemctl stop ollama.service times out
|
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As described, when I try to stop the systemd unit on Fedora linux from ollama (current version), I get this:
Failed to stop ollama.service: Connection timed out
|
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PR_kwDOJ0Z1Ps59MxUY
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|
Fixing generate failure due to global gpgsign setting
|
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Hi all, first time commit here so please let me know if I'm missing anything.
Found a small issue in the generate script for `llama.cpp` where the script patches with a placeholder user. Since I have `commit.gpgsign` enabled globally on my system, this was causing the following error during `go generate ./...`.
```
$ go generate ./...
<snip>
+ git submodule init
+ git submodule update --force ../llama.cpp
Submodule path '../llama.cpp': checked out '8962422b1c6f9b8b15f5aeaea42600bcc2d44177'
+ apply_patches
+ for patch in ../patches/*.patch
+ git -c user.name=nobody -c 'user.email=<>' -C ../llama.cpp am ../patches/0000-cmakelist.patch
Applying: patch cmakelist
error: gpg failed to sign the data:
gpg: skipped "nobody <>": No secret key
[GNUPG:] INV_SGNR 9 nobody <>
[GNUPG:] FAILURE sign 17
gpg: signing failed: No secret key
fatal: failed to write commit object
llm/generate/generate_linux.go:3: running "bash": exit status 128
```
Since this happens in a submodule, setting `commit.gpgsign` to `false` for the top-level git repository does not have any effect.
A workaround in the meantime is to disable global gpg signing temporarily, I.E.
```
git config --global commit.gpgsign false
go generate ./...
git config --global commit.gpgsign true
```
Cheers!
|
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I_kwDOJ0Z1Ps5_npcM
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|
Use pkg-config to find llama-cpp libs
|
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Hi first of all, thank you for ollama, its amazing !
Im one of the person trying to maintain this on nixos. Since 0.1.19 i think llama-cpp is directly included as a submodule in the repo. Also the .so objects are directly referenced by path in the go build files. Would it be possible to use pkg-config to find those files ?
This would make building ollama from source much easier as llama-cpp can just be specified as a dependency.
I understand that you might have a million more important things to do, i just want to start the discussion.
|
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I_kwDOJ0Z1Ps6OieZm
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Running Hugging Face Models
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| 2024-07-04T19:54:54
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NONE
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Hi team,
Can we load Hugging Face models directly using ollama?
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| 2024-12-07T17:11:44
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NONE
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### What is the issue?
Report date: 2024-11-07
During a custom compile of ollama 0.4.0 on Linux (POP OS 22.04) for AMD ROCm GPUs (AMD 6650 GPU), the initial compile works.
However, when trying to execute the go compile, the compile fails after about two minutes citing exit code 1 and saying the error is unable to find ggml_rocm.
ROCm 6.0
### OS
Linux
### GPU
AMD
### CPU
AMD
### Ollama version
0.4.0
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I_kwDOJ0Z1Ps501VUi
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Multline editing prior lines not possible
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NONE
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I would like to edit the text pasted after the multiline delimiter editable such that I can go back on previous lines to edit.
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I_kwDOJ0Z1Ps6SFbTR
| 6,200
|
Support --mlock on the command line. Also there are undocumented model file parameters
|
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| 2024-08-06T13:28:28
| 2024-08-06T13:31:54
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### What is the issue?
The original issue was that my Mac was experiencing an exponential slow down. Upon investigating the issue I noticed my RAM usage was very, very low, but my swap was climbing at the rate of about 1GB per 1K of filled context.
In the end I discovered the --mlock flag in llama.cpp.
I was in discord asking for help setting it since the command line Ollama straight up rejects it.
Eventually we discovered that this is controlled by the model file parameter use_mlock
Except that appears to be undocumented. In the same space I found a few other undocumented parameters.
So in a nutshell, it would lovely if you could add --mlock to the command line since I don't want to have to edit every model file. Also if you could update the docs so use_mlock and the other undocumented parameters are documented, that would be awesome.
Thanks for your hard work and such a great product!
### OS
macOS
### GPU
Intel
### CPU
Intel
### Ollama version
0.3.3
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I_kwDOJ0Z1Ps56fMIF
| 1,694
|
Windows build is broken.
|
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| 2023-12-24T06:06:33
| 2024-01-06T03:34:21
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|
CONTRIBUTOR
|
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```bash
go build .
# github.com/jmorganca/ollama/llm
llm\llm.go:83:17: undefined: gpu.GetGPUInfo
llm\llm.go:89:9: undefined: nativeInit
llm\llm.go:92:109: undefined: extServer
llm\llm.go:94:15: undefined: newDynamicShimExtServer
llm\llm.go:101:9: undefined: newDefaultExtServer
llm\llama.go:211:24: undefined: libEmbed
llm\llama.go:218:19: undefined: libEmbed
```
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Notify systemd that ollama server is ready
|
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| 2024-09-12T13:19:22
| 2024-11-12T00:46:20
| 2024-11-12T00:46:19
|
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I_kwDOJ0Z1Ps6RPJMn
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|
change client app installation path on windows
|
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| 2024-07-30T00:55:24
| 2024-07-30T17:13:54
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At present, when installing ollama windows preview version, there is only a default installation path(C:/users/user/local/..), which is unchangeable Hopefully, there would be another option for installation path.
|
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I_kwDOJ0Z1Ps6BEcqZ
| 2,896
|
View Model Licenses on the Model Registry / Library Page
|
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| 2024-03-03T15:55:33
| 2024-03-04T08:05:16
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NONE
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Hi! I was just poking around at all the amazing models you have listed on your growing registry.
From a quality-of-life perspective, would be great to see the licenses at a glance available at this page: https://ollama.com/library
I see a similar issue as this had been closed referring to a post-download inspectable license: https://github.com/ollama/ollama/issues/1509
For various reasons this doesn't solve the quality-of-life issue, not because it's on the cli, but because it requires downloading the model to inspect the license.
Thanks!
Steven
|
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I_kwDOJ0Z1Ps5yJPr9
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is there any plan to provide GUI interface?
|
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| 2023-09-27T08:54:58
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NONE
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is there any plan to provide GUI interface for ollama?
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I_kwDOJ0Z1Ps6jxEIf
| 8,155
|
Clarification: "format" vs "tools" behaviours
|
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| 2024-12-18T11:25:11
| 2024-12-20T21:48:59
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### What is the issue?
Structured output formatting was recently released. There are now 2 different ways of structuring your output:
1. Pass a schema to the "format" argument to the API.
2. Convert the schema to a tool and pass it to the "tools" argument to the API.
I understand that semantically, for structured output, it would make more sense to use the "format" option, whereas for tool use, the "tools" argument is more sensible.
My question is if there is any difference under the hood?
Specifically, I have the following questions:
- Does `tools` insert the tool into the prompt using the tool tokens in the model chat template?
- Does "format" insert the tool into the prompt using the tool tokens in the model chat template?
- Does "format" ensure that the schema is respected, or only that the output is "json", but not necessarily "json" that complies to the schema? Is the behaviour exactly the same for "tools", or is there a difference?
### OS
Linux
### GPU
_No response_
### CPU
_No response_
### Ollama version
0.5.4
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I_kwDOJ0Z1Ps6lg4q6
| 8,356
|
Allow context to be set from the command line.
|
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[] | null | 5
| 2025-01-09T05:22:14
| 2025-01-27T18:24:04
| 2025-01-11T00:05:50
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I have a shell script called wizard that is simply
```
more ~/bin/wizard
#!/bin/bash
ollama run llama3.2
```
It's a very useful script but I would like it to be able to set the context to a larger amount something like
```
ollama run llama3.2 --num_ctx 4096
```
Current docs:
```How can I specify the context window size?
By default, Ollama uses a context window size of 2048 tokens.
To change this when using ollama run, use /set parameter:
/set parameter num_ctx 4096
When using the API, specify the num_ctx parameter:
curl http://localhost:11434/api/generate -d '{
"model": "llama3.2",
"prompt": "Why is the sky blue?",
"options": {
"num_ctx": 4096
}
}'
````
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| 2,788,385,663
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I_kwDOJ0Z1Ps6mM2N_
| 8,429
|
How do we EXPORT ollama responses to file TXT/JSON ?
|
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"repos_url": "https://api.github.com/users/GAC-Machine/repos",
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"type": "User",
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[] | null | 1
| 2025-01-14T22:18:54
| 2025-01-28T21:16:32
| 2025-01-28T21:16:32
|
NONE
|
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| null | null | null |
OS : Windows 11 Pro
Model: ollama 3.2
Want to create logregistry file (trivially a txt/JSON file).
I want a JSON structured file like:
```
{
"Model" : "name_of-model",
"running environment" : "Win-MacOS-Linux",
"conversation": [
"prompt1" : "my_input_text"
"response1" : "ollama_output_text"
},
... //so on
]
}
```
Alternatively it would be adequate a txt file like:
```
Model name_of_model
Running environment Win_MacOS_Linux
ConversationID Prompt-Input Response-Output
00000001 [my_input_text] [ollama_output_text]
```
Referencing this issue on Github https://github.com/ollama/ollama/issues/1710 dated #Dec, 25, 2023.
The command provided is for Unix-Like system (that is Linux, MacOS).
`ollama run llama3.2 "prompt" >> response.txt`
What about Windows ?
I tried it, but it doesn't work.
|
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PR_kwDOJ0Z1Ps52l6sH
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|
llm: keep patch for llama 3 rope factors
|
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| 2024-07-26T15:16:34
| 2024-07-26T22:20:54
| 2024-07-26T22:20:53
|
MEMBER
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I_kwDOJ0Z1Ps6mRKhG
| 8,441
|
Segmentation fault
|
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NONE
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| null | null | null |
### What is the issue?
Dear Ollama Team,
I encountered an issue while attempting to run the 'ollama service' command after installation. Here are the detailed steps I followed and the error message I received:
1. I downloaded the 'ollama-linux-amd64.tgz' file from your official source because my research network has some access limitations.
2. I unzipped the file to the path '/usr/local/bin/ollama'.
3. When I executed the command 'ollama service', I encountered a 'Segmentation fault' error.
I would appreciate it if you could look into this issue and provide any possible solutions or workarounds. Thank you for your attention to this matter.
Best regards
### OS
Linux
### GPU
Nvidia
### CPU
_No response_
### Ollama version
_No response_
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I_kwDOJ0Z1Ps50z7Vc
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|
permissions error on `ollama create` on Linux
|
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| 2023-10-24T17:47:57
| 2023-11-16T00:41:14
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|
MEMBER
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On Linux, Ollama runs as another `ollama` user. This causes permission errors on `ollama create`.
A fix is in progress, tracked here: https://github.com/jmorganca/ollama/issues/891
In the meantime, current workaround is to add `ollama` to the user's group so Ollama can access group-accessible files:
```
usermod -a -G $(id -gn $USER) ollama
```
Then re-start the `ollama` service
```
sudo systemctl restart ollama
```
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I_kwDOJ0Z1Ps6LkReu
| 4,927
|
Support for zpoint_large_embedding_zh
|
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[https://huggingface.co/iampanda/zpoint_large_embedding_zh](https://huggingface.co/iampanda/zpoint_large_embedding_zh)
Thanks.
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PR_kwDOJ0Z1Ps5tyTmk
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Fix release CI
|
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download-artifact path was being used incorrectly. It is where to extract the zip not the files in the zip to extract. Default is workspace dir which is what we want, so omit it
|
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I_kwDOJ0Z1Ps6LhhfR
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Error: llama runner process has terminated: signal: aborted (core dumped)
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| 2024-06-07T16:39:11
| 2024-08-26T09:59:17
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### What is the issue?
When I run the CLI ollama run qwen2:72b-instruct-q2_K
then download the model and run the model。
rError: llama runner process has terminated: signal: aborted (core dumped)
### OS
Linux
### GPU
Nvidia
### CPU
Intel
### Ollama version
0.1.38
|
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PR_kwDOJ0Z1Ps5prcOi
| 3,153
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Exporting Ollama to WebAssembly
|
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NONE
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This PR exports ollama as a WebAssembly Host Module.
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PR_kwDOJ0Z1Ps5gDjSx
| 1,225
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add Llama Coder
|
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CONTRIBUTOR
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Hey, i have created a plugin for VS Code that integrates with ollama!
|
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GPTQ / ExLlamaV2 (EXL2) quantisation
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| 2023-11-22T06:12:08
| 2024-08-15T14:24:39
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# Feature Description
Please provide a detailed written description of what you were trying to do, and what you expected `llama.cpp` to do as an enhancement.
# Motivation
It sounds like it's a fast/useful quantisation method:
- https://towardsdatascience.com/exllamav2-the-fastest-library-to-run-llms-32aeda294d26
- https://github.com/mlabonne/llm-course/blob/main/Quantize_models_with_ExLlamaV2.ipynb
- https://towardsdatascience.com/4-bit-quantization-with-gptq-36b0f4f02c34
- https://huggingface.co/blog/gptq-integration
- https://oobabooga.github.io/blog/posts/gptq-awq-exl2-llamacpp/
- > A detailed comparison between GPTQ, AWQ, EXL2, q4_K_M, q4_K_S, and load_in_4bit: perplexity, VRAM, speed, model size, and loading time.
## See Also
- https://github.com/ggerganov/llama.cpp/issues/4165
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I_kwDOJ0Z1Ps6amWbq
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Add nemotron-4-340b-instruct
|
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Since we recently discovered how good LLAMA 3.1 70B Nemotron is, maybe we could consider adding the 340B model... for those with abundant GPU resources - are there any?
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I_kwDOJ0Z1Ps6nlyig
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Error: llama runner process has terminated: error loading model: unable to allocate CUDA0 buffer (4x L40S, 384GB system RAM, Deepseek-R1)
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### What is the issue?
I am aware that 4 x L40S only has 192GB of VRAM, but the machine also has 384GB of system RAM. The error seems to indicate that 45108 MiB of RAM is being allocated with cudaMalloc and this is failing. This is very close to the GPU limit (46068 MiB). On my home setup (2x P40, admittedly not trying such a huge model) the GPU never gets close to its VRAM limit (typically only 22GB out of 24GB).
```
Jan 26 17:48:20 ip-172-31-3-6 ollama[1418]: llm_load_print_meta: rope_yarn_log_mul = 0.1000
Jan 26 17:50:35 ip-172-31-3-6 ollama[1418]: ggml_backend_cuda_buffer_type_alloc_buffer: allocating 45108.64 MiB on device 0: cudaMalloc failed: out of memory
Jan 26 17:50:35 ip-172-31-3-6 ollama[1418]: llama_model_load: error loading model: unable to allocate CUDA0 buffer
Jan 26 17:50:35 ip-172-31-3-6 ollama[1418]: llama_load_model_from_file: failed to load model
Jan 26 17:51:23 ip-172-31-3-6 ollama[1418]: panic: unable to load model: /usr/share/ollama/.ollama/models/blobs/sha256-9801e7fce27dbf3d0bfb468b7b21f1d132131a546dfc43e50518631b8b1800a9
Jan 26 17:51:23 ip-172-31-3-6 ollama[1418]: goroutine 34 [running]:
Jan 26 17:51:23 ip-172-31-3-6 ollama[1418]: github.com/ollama/ollama/llama/runner.(*Server).loadModel(0xc0001a0000, {0x1b, 0x0, 0x0, 0x0, {0xc000194090, 0x4, 0x4}, 0xc00018a060, 0x0}, ...)
Jan 26 17:51:23 ip-172-31-3-6 ollama[1418]: github.com/ollama/ollama/llama/runner/runner.go:852 +0x3ad
Jan 26 17:51:23 ip-172-31-3-6 ollama[1418]: created by github.com/ollama/ollama/llama/runner.Execute in goroutine 1
Jan 26 17:51:23 ip-172-31-3-6 ollama[1418]: github.com/ollama/ollama/llama/runner/runner.go:970 +0xd0d
Jan 26 17:51:24 ip-172-31-3-6 ollama[1418]: time=2025-01-26T17:51:24.077Z level=INFO source=server.go:589 msg="waiting for server to become available" status="llm server error"
Jan 26 17:51:24 ip-172-31-3-6 ollama[1418]: time=2025-01-26T17:51:24.578Z level=ERROR source=sched.go:455 msg="error loading llama server" error="llama runner process has terminated: error loading model: unable to allocate CUDA0 buffer\nllama_load_model_from_file: failed to load model"
Jan 26 17:51:24 ip-172-31-3-6 ollama[1418]: [GIN] 2025/01/26 - 17:51:24 | 500 | 3m6s | 127.0.0.1 | POST "/api/generate"
Jan 26 17:51:30 ip-172-31-3-6 ollama[1418]: time=2025-01-26T17:51:30.190Z level=WARN source=sched.go:646 msg="gpu VRAM usage didn't recover within timeout" seconds=5.6116838510000004 model=/usr/share/ollama/.ollama/models/blobs/sha256-9801e7fce27dbf3d0bfb468b7b21f1d132131a546dfc43e50518631b8b1>
Jan 26 17:51:30 ip-172-31-3-6 ollama[1418]: time=2025-01-26T17:51:30.947Z level=WARN source=sched.go:646 msg="gpu VRAM usage didn't recover within timeout" seconds=6.369278328 model=/usr/share/ollama/.ollama/models/blobs/sha256-9801e7fce27dbf3d0bfb468b7b21f1d132131a546dfc43e50518631b8b1800a9
Jan 26 17:51:31 ip-172-31-3-6 ollama[1418]: time=2025-01-26T17:51:31.707Z level=WARN source=sched.go:646 msg="gpu VRAM usage didn't recover within timeout" seconds=7.128851916 model=/usr/share/ollama/.ollama/models/blobs/sha256-9801e7fce27dbf3d0bfb468b7b21f1d132131a546dfc43e50518631b8b1800a9
Jan 26 17:51:40 ip-172-31-3-6 ollama[1418]: [GIN] 2025/01/26 - 17:51:40 | 200 | 65.972µs | 127.0.0.1 | GET "/api/version"
ubuntu@ip-172-31-3-6:~$ ollama --version
ollama version is 0.5.7
ubuntu@ip-172-31-3-6:~$ free
total used free shared buff/cache available
Mem: 390837004 4152012 385439624 3248 1245368 383763992
Swap: 0 0 0
ubuntu@ip-172-31-3-6:~$ nvidia-smi
Sun Jan 26 17:48:08 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.144.03 Driver Version: 550.144.03 CUDA Version: 12.4 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA L40S On | 00000000:38:00.0 Off | 0 |
| N/A 22C P8 22W / 350W | 4MiB / 46068MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 NVIDIA L40S On | 00000000:3A:00.0 Off | 0 |
| N/A 22C P8 21W / 350W | 4MiB / 46068MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 2 NVIDIA L40S On | 00000000:3C:00.0 Off | 0 |
| N/A 22C P8 44W / 350W | 4MiB / 46068MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 3 NVIDIA L40S On | 00000000:3E:00.0 Off | 0 |
| N/A 23C P8 22W / 350W | 4MiB / 46068MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
```
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.5.7
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I_kwDOJ0Z1Ps6TD-Sg
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Please add socks5 proxy func to download models ！Because the internet in China is not accessible
|
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Please add socks5 proxy func to download models ！Because the internet in China is not accessible
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PR_kwDOJ0Z1Ps5jZCzz
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Update README.md - Community Integrations - Ollama for Ruby
|
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| 2024-01-06T21:26:22
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CONTRIBUTOR
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Hi!
Adding a new library for the Ruby language:
- [Ollama for Ruby](https://github.com/gbaptista/ollama-ai)
- [Ruby Gem](https://rubygems.org/gems/ollama-ai)
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Support model allenai/OLMoE-1B-7B-0924
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i want check performance this model(MoE)
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PR_kwDOJ0Z1Ps5oWsKe
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Fix embeddings load model behavior
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Fixes https://github.com/ollama/ollama/issues/2810. Also cleans up the `embedding_only` API option which had no effect.
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PR_kwDOJ0Z1Ps5mhy_l
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replace strings buffer with hasher
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the buffered value is going into the hasher eventually so write directly to the hasher instead
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I_kwDOJ0Z1Ps5vWe4L
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llamma.cpp breaking change deprecating GGML in favor of GGUF
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Note that the upstream llama.cpp project has now completely deprecated GGML in favor of GGUF [1].
How should the repository and user models adapt to this?
[1] https://github.com/ggerganov/llama.cpp/pull/2398
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Main
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I_kwDOJ0Z1Ps591Ltv
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Error: unmarshal
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Noticing a `Error: unmarshal: invalid character 'p' after top-level value` on `ollama run llava`
<img width="923" alt="image" src="https://github.com/ollama/ollama/assets/18315/84f04d3e-a64e-4da5-9131-20ccf56cdeca">
`client version is 0.1.22`
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Colons in hostname cause an error on Windows
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| 2024-05-01T19:36:20
| 2024-05-02T17:53:48
| null |
MEMBER
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### What is the issue?
Including a colon in the hostname such as `localhost:6000/my/model` causes an error on windows:
```
$ ollama create -f ../models/Modelfile localhost:3000/library/tmp
transferring model data
reading model metadata
creating template layer
using already created layer sha256:4fed7364ee3e0c7cb4fe0880148bfdfcd1b630981efa0802a6b62ee52e7da97e
using already created layer sha256:fa8235e5b48faca34e3ca98cf4f694ef08bd216d28b58071a1f85b1d50cb814d
using already created layer sha256:d47ab88b61ba20ed39a1b205a7d5a8e201dcf09107e6b05f128778c32baa4a69
using already created layer sha256:e14c21df1d1c6baff291558d0da327e5aabe4d4e7dd97bc1bf173e535f2ab210
using already created layer sha256:cb4e88e025cabd86f873cd94972dc82cfd883336b2294882a5c28af996a4db92
writing manifest
Error: mkdir C:\Users\jmorg\.ollama\models\manifests\localhost:3000: The directory name is invalid.
```
### OS
Windows
### GPU
_No response_
### CPU
_No response_
### Ollama version
_No response_
| null |
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PR_kwDOJ0Z1Ps5WXbPk
| 212
|
fix multiline string
|
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| 2023-07-25T18:52:00
| 2023-07-25T18:53:55
| 2023-07-25T18:53:51
|
CONTRIBUTOR
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the data needs to remove the multiline quotes but include the command:
e.g.
```
TEMPLATE """
my template values
"""
```
should be
```
TEMPLATE
my template values
```
after scanning
|
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| 2,554,099,512
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I_kwDOJ0Z1Ps6YPHc4
| 7,018
|
AMD Radeon Pro 5700 XT 16GB GPU Support
|
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| 2024-09-28T08:04:16
| 2024-09-28T22:44:04
| 2024-09-28T22:44:04
|
NONE
|
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| null | null | null |
Hi,
Would it be possible to add support for AMD Radeon Pro 5700 XT 16GB VRAM GPU?
System: macOS Sequoia
CPU: 3,8 GHz 8-Core Intel Core i7
RAM: 128GB
Currently when using such hardware Ollama utilizes only CPU.
The system is from 2020, but it is still a capable machine.
Best,
|
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I_kwDOJ0Z1Ps6dwN7m
| 7,592
|
Wrong Prompt Token Report from Ignoring Image Token Count
|
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| 2024-11-09T23:31:37
| 2024-11-11T18:47:55
| 2024-11-11T18:47:54
|
NONE
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### What is the issue?
If you run llama3.2-vision with /set verbose, it looks like it only counts tokens for text ignoring tokens from image. Thus it reports extremely slow speed for prompt rate.
It's the same with API.
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
0.4.0
|
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|
AMD Gpu RX 6600 on WIndows 10
|
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| 2024-05-11T03:06:41
| 2024-05-11T04:47:20
| 2024-05-11T04:23:49
|
NONE
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### What is the issue?
I'm having trouble using my AMD GPU RX 6600 on Windows 10 with Ollama. Could someone please assist me and provide any workarounds to make this AMD GPU RX 6600 function?
Please provide step-by-step instructions specifically for Windows 10. Thank you.
### OS
Windows
### GPU
AMD
### CPU
Intel
### Ollama version
0.1.35
|
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I_kwDOJ0Z1Ps5rABN2
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|
crash on large context sizes
|
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| 2023-07-08T23:43:30
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MEMBER
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For prompts larger than ~100 tokens the server will sometimes crash
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I_kwDOJ0Z1Ps58Kj9n
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|
Ollama not using my gpu whatsoever.
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NONE
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I do have cuda drivers installed:
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PR_kwDOJ0Z1Ps5YvLqL
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Build Automation
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| 2023-09-14T20:33:47
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CONTRIBUTOR
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Working on moving our builds to a github runner on release. This is a CPU amd64 build.
No arm64 in this PR because github doesn't have an arm64 runner, but we need to build the llama.cpp exe on an arm64 machine for the arm64 release. We can use an external build runner to accomplish this.
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I_kwDOJ0Z1Ps6kgGDb
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|
DeepSeek v3
|
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| 2024-12-26T15:13:45
| 2025-01-15T15:30:59
| 2025-01-14T00:26:00
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CONTRIBUTOR
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https://huggingface.co/deepseek-ai/DeepSeek-V3-Base
https://huggingface.co/deepseek-ai/DeepSeek-V3
Kindly make it available to ollama so we can test..
Model paper
https://github.com/deepseek-ai/DeepSeek-V3/blob/main/DeepSeek_V3.pdf
https://x.com/deepseek_ai/status/1872242657348710721
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PR_kwDOJ0Z1Ps5j89Is
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|
Add MindMac to Community Integrations -> Web & Desktop section
|
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Hi there,
MindMac is a privacy-first & feature-rich GPT client for macOS, designed for maximum productivity. It already has Ollama support, enabling users to run any model on their devices and easily connect with MindMac to ask questions seamlessly. Quick documentation can be found [here](https://docs.mindmac.app/how-to.../add-ollama-endpoint). Please help to review this PR. Thank you in advance.
Best regards,
Hoang
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Ollama downloading wrong driver.
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| 2024-05-24T17:32:21
| 2024-06-18T13:41:19
| 2024-06-18T13:40:08
|
NONE
|
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| null | null | null |
### What is the issue?
Ollama is downloading NVIDIA drivers even though I have AMD GPU.
I have ROCM installed
```
apt show rocm-libs -a
Package: rocm-libs
Version: 6.1.1.60101-90~22.04
```
and I use the following script to setup [Ollama](https://ollama.com/download/linux)
` curl -fsSL https://ollama.com/install.sh | sh`
The output of running the script
```
curl -fsSL https://ollama.com/install.sh | sh
>>> Downloading ollama...
######################################################################## 100.0%##O=# # ######################################################################## 100.0%
>>> Installing ollama to /usr/local/bin...
[sudo] password for ----:
>>> Creating ollama user...
>>> Adding ollama user to render group...
>>> Adding ollama user to video group...
>>> Adding current user to ollama group...
>>> Creating ollama systemd service...
>>> Enabling and starting ollama service...
Created symlink /etc/systemd/system/default.target.wants/ollama.service → /etc/systemd/system/ollama.service.
>>> NVIDIA GPU installed.
```
### OS
Linux
### GPU
AMD
### CPU
AMD
### Ollama version
N/A
|
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| 1,822,635,478
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I_kwDOJ0Z1Ps5sozXW
| 218
|
CLI doesn't install properly if app isn't named `Ollama.app`
|
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| 2023-07-26T15:14:05
| 2023-07-27T14:53:42
| 2023-07-27T14:53:42
|
MEMBER
|
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If the app filename has a space in it (e.g. `Ollama 2.app`), the cli won't install itself in `/usr/local/bin/ollama` properly
|
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| 2,160,454,556
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PR_kwDOJ0Z1Ps5oQGF_
| 2,827
|
fix: print usedMemory size right
|
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| 2024-02-29T06:02:07
| 2024-02-29T19:11:12
| 2024-02-29T19:11:05
|
CONTRIBUTOR
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