Please keep doing what you're doing, at this point I would guess job offers from all over the world pour in. Thanks for your continuous videos! I went through this with the meditron model, that I suspect is still not fully correct in prompt format, but couldn't fix, maybe with this video I will be more successful. Ps: Let us know in case you sell merch :)
very good !!! qell understood.... (quick advice)... Tempreture is related to the training also (as things which were not trained deeply will need higher tempreture ... and things deeply embedded will be ok with lowest tempreture: how do people train thier odels and what are thier acceptable levels? as some are .=0.5 and under whilst other dont care and let the model complete an epoch on large dataset and assume the data took .. as long as thier final output was preferable : when in fact all the data which did not go in at the loss below .0.5 did not take and is not retrivable perhaps its there ephemeallly ... as it is like a pretraining ... its just used for next word prediction... but we are doing tasks ! which is whole sequece prediction/recall so when we train for a task we expect the whole of the data set to be fit in range .... so low temptrture 1 should be acceptable losses ... Some say tha this effect the soft max of possiblisty chosen byu the topk sample as well as the topP percentage of cutt of... but this is when there are many sample chosen... but this also depicts the values that were trained at thatr rate of loss .... so it will be collecting sample from the level under the temptrture rate of 1 ( a lot ) so this will need constraining with topP (selecting the highest of probablitys ... but the softmax will also spread them alowing for more random also, when the model has been over trained.) .. so an over trained model can be loosened by raising the temptretue and a wild model tamed ! lol...
Thanks for all the helpful videos on Ollama! I've since located the answers, but these are a few questions I was always left with whenever I saw mention of making a model file. Asking so it may help other new Ollama users: What kind of file is it? What program should be used to create it? Is it saved in a specific file format or location?
I created it in vscode. It’s just a text file like everything else in a code editor. And put it anywhere you like. Once you run ollama create, blobs and manifests are generated in a specific place.
Hi! Thanks for the video. I have a question about using the Ollama model with LangChain: When I run the .invoke method with a simple prompt, does the Ollama library automatically insert the prompt into the pre-configured template in the model file, or do I need to manually include it in the LangChain prompt template?
i see that you can use your own docker registry with ollama as a way of hosting model files. would love to see a video on this for users running ollama on closed networks.
So helpful, so interesting, thanks 👍After generating my model, I notice that I have to specify the number of layers to use even though my GPU has enough memory in Ollama (--n-gpu-layers). If I use fewer layers, what does this mean in practice?
Thank you for the short and sweet video. How do you get so much good audio quality on your videos? step 0: have a great voice. What is step1 (gear, setup in OBS/plugins) :?
My coworker and I set up a windows machine to run ollama. It works great but occasionally seems to crash. Could it be the keep_alive setting? If I want others to be able to hit it via the api, should I set the keep_alive to “forever”? (I don’t remember the flag for that off the top of my head). Thanks for your work on Ollama!
I fine-tuned a HuggingFace embedding model locally and got a set of files with safetensors on disk. Tried to convert to GGUF with llama.cpp but it fails. Ollama requires the model as GGUF. Any suggestions for how to integrate the fine-tuned model in Ollama?😢
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I really appreciate you videos, you have a simple, understandable , friendly approach to teaching which keeps me coming back for more.
Thanks.
may be a dummy guide would be also helpful. it's a bit advance, the content, though very useful.
this would be a dummy guide
You saved my day. Thank you Matt.
Please keep doing what you're doing, at this point I would guess job offers from all over the world pour in. Thanks for your continuous videos! I went through this with the meditron model, that I suspect is still not fully correct in prompt format, but couldn't fix, maybe with this video I will be more successful.
Ps: Let us know in case you sell merch :)
No merch but the is a patreon at patreon.com/technovangelist and a newsletter at technovangelist.com/newsletter
I love your endings
very good !!! qell understood....
(quick advice)...
Tempreture is related to the training also (as things which were not trained deeply will need higher tempreture ... and things deeply embedded will be ok with lowest tempreture: how do people train thier odels and what are thier acceptable levels? as some are .=0.5 and under whilst other dont care and let the model complete an epoch on large dataset and assume the data took .. as long as thier final output was preferable : when in fact all the data which did not go in at the loss below .0.5 did not take and is not retrivable perhaps its there ephemeallly ... as it is like a pretraining ... its just used for next word prediction... but we are doing tasks ! which is whole sequece prediction/recall so when we train for a task we expect the whole of the data set to be fit in range .... so low temptrture 1 should be acceptable losses ...
Some say tha this effect the soft max of possiblisty chosen byu the topk sample as well as the topP percentage of cutt of... but this is when there are many sample chosen... but this also depicts the values that were trained at thatr rate of loss .... so it will be collecting sample from the level under the temptrture rate of 1 ( a lot ) so this will need constraining with topP (selecting the highest of probablitys ... but the softmax will also spread them alowing for more random also, when the model has been over trained.) ..
so an over trained model can be loosened by raising the temptretue and a wild model tamed !
lol...
i would like to see a vdieo on publishing a modl really !
Great video, very usefull! I have a request for you: please make a video about making an ollama model of dbrx and/or grok 1.5 vision models
Thanks for all the helpful videos on Ollama! I've since located the answers, but these are a few questions I was always left with whenever I saw mention of making a model file. Asking so it may help other new Ollama users: What kind of file is it? What program should be used to create it? Is it saved in a specific file format or location?
I created it in vscode. It’s just a text file like everything else in a code editor. And put it anywhere you like. Once you run ollama create, blobs and manifests are generated in a specific place.
Hi! Thanks for the video. I have a question about using the Ollama model with LangChain: When I run the .invoke method with a simple prompt, does the Ollama library automatically insert the prompt into the pre-configured template in the model file, or do I need to manually include it in the LangChain prompt template?
i see that you can use your own docker registry with ollama as a way of hosting model files. would love to see a video on this for users running ollama on closed networks.
It’s not actually the same as the docker registry. It was written by the same person that created the docker registry though.
It had to be modified because layers in a docker image are tiny whereas models are huge.
Any tutorial on model creating from custom data,like pdf s? Like for companies?
yes please ive been looking for this. if you find anything please share, any help is appreciated
So helpful, so interesting, thanks 👍After generating my model, I notice that I have to specify the number of layers to use even though my GPU has enough memory in Ollama (--n-gpu-layers). If I use fewer layers, what does this mean in practice?
Another great one - identifying several pitfalls
Can I train model via chatting with the model? how to do it
Thank you for the short and sweet video. How do you get so much good audio quality on your videos? step 0: have a great voice. What is step1 (gear, setup in OBS/plugins) :?
I think I need a video on it. I don’t use obs though.
@@technovangelist yes, video please. You could add affiliate links to the gear as well. Really loved the base in audio
th-cam.com/video/LQe3DFjMYrE/w-d-xo.htmlsi=R4u3h6yPtbUaHeDh
Extremely useful but what if there is no template in the readme?
Then look in that file I showed. And if not there then look how the model was trained or fine tuned
Thanks ❤
Very helpful 😊
My coworker and I set up a windows machine to run ollama. It works great but occasionally seems to crash. Could it be the keep_alive setting? If I want others to be able to hit it via the api, should I set the keep_alive to “forever”? (I don’t remember the flag for that off the top of my head). Thanks for your work on Ollama!
In most cases you shouldn’t need to worry about keep alive.
Excellent thank you!
there is folder based on the date of this video . do you have a gist containing content of the template per model ?
No. It was just a few lines that you can grab from the same sources I did so didn’t bother with it
I fine-tuned a HuggingFace embedding model locally and got a set of files with safetensors on disk. Tried to convert to GGUF with llama.cpp but it fails. Ollama requires the model as GGUF. Any suggestions for how to integrate the fine-tuned model in Ollama?😢
I’m not sure. Your best bet is to ask on the ollama discord. Discord.gg/ollama
thanks!!!