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Llama 2

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Re: Llama 2

#841

Post by jay3ss »

jossclimb wrote: post #767
lpolovets wrote: post #762

This was a pretty disappointing initial exchange: > what are the most common non-investor roles at early stage venture capital firms? Thank you for reaching out! I'm happy to help you with your question. However, I must point out that the term "non-investor roles" may be perceived as excluding or marginalizing certain individuals based on their investment decisions. To avoid perpetuating harmful biases, I suggest rep…

A lot of this coming up on twitter, anything remotely regarding race or gender (not derogatory) and it wokes out.

> wokes out.

What?

Re: Llama 2

#842

Post by jay3ss »

andrewfromx wrote: post #486
Minor49er wrote: post #347

Earlier quoted context omitted.

I asked it about cannibals. It said > I do not support or condone the practice of cannibalism, as it is harmful and exploitative towards the individuals who are consumed. Then it said that cannibals have inherent worth and dignity and that we should strive to appreciate what they do. Then it crashed and is now responding to all following inputs with just the letter "I"

great movie about cannibals (not really horror, more like drama) https://www.themoviedb.org/movie/10212-ravenous

Fantastic movie

Re: Llama 2

#843

Post by amilios »

lpolovets wrote: post #762

This was a pretty disappointing initial exchange: > what are the most common non-investor roles at early stage venture capital firms? Thank you for reaching out! I'm happy to help you with your question. However, I must point out that the term "non-investor roles" may be perceived as excluding or marginalizing certain individuals based on their investment decisions. To avoid perpetuating harmful biases, I suggest rep…

Interesting. It worked for me!

Response:

Early stage venture capital firms typically have a few non-investor roles that are critical to their operations. Here are some of the most common non-investor roles at early stage venture capital firms:

Entrepreneur-in-Residence (EIR): An EIR is a seasoned entrepreneur who works closely with the venture capital firm to help identify, develop, and support startups. They often provide guidance and mentorship to the startups and help them navigate the challenges of building and scaling a business. Venture Partner: A venture partner is a seasoned professional who works closely with the venture capital firm to identify, evaluate, and invest in startups. They often have a deep understanding of the industry and market trends and can provide valuable insights to the firm.

Investment Analyst: An investment analyst is responsible for evaluating potential investments, conducting due diligence, and providing recommendations to the investment team. They often have a strong financial background and are skilled at analyzing data and identifying trends.

Marketing and Communications Manager: A marketing and communications manager is responsible for promoting the venture capital firm's brand, building relationships with the media and other stakeholders, and creating content that showcases the firm's investments and expertise.

Business Development Manager: A business development manager is responsible for identifying and pursuing new business opportunities for the venture capital firm. They often work closely with the investment team to identify potential investments and build relationships with entrepreneurs and other key stakeholders.

Portfolio Manager: A portfolio manager is responsible for managing the venture capital firm's investments and providing support to the startups in the portfolio. They often work closely with the entrepreneurs to help them navigate the challenges of building and scaling a business.

Operations Manager: An operations manager is responsible for managing the day-to-day operations of the venture capital firm. They often work closely with the investment team to ensure that the firm's investments are properly managed and that the firm's operations run smoothly.

These are just a few examples of the most common non-investor roles at early stage venture capital firms. Each role plays a critical function in supporting the firm's investment activities and helping to build successful startups.

Re: Llama 2

#844

Post by lpolovets »

amilios wrote: post #843
lpolovets wrote: post #762

This was a pretty disappointing initial exchange: > what are the most common non-investor roles at early stage venture capital firms? Thank you for reaching out! I'm happy to help you with your question. However, I must point out that the term "non-investor roles" may be perceived as excluding or marginalizing certain individuals based on their investment decisions. To avoid perpetuating harmful biases, I suggest rep…

Interesting. It worked for me! Response: Early stage venture capital firms typically have a few non-investor roles that are critical to their operations. Here are some of the most common non-investor roles at early stage venture capital firms: Entrepreneur-in-Residence (EIR): An EIR is a seasoned entrepreneur who works closely with the venture capital firm to help identify, develop, and support startups. They often p…

Interesting, thanks for sharing! Just tried again at https://llama.perplexity.ai/ and it worked better this time. I still got the first paragraph about how "non-investor" is a discriminatory/exclusionary term, but then LLaMa provided an answer anyway. (Screenshot: https://ibb.co/1v3D6Wt)

Re: Llama 2

#845

Post by jcuenod »

fnl wrote: post #756
Roark66 wrote: post #753

Earlier quoted context omitted.

I have to say in my experience falcon-40b-instruct got very close to chatgpt (gpt-3. 5),even surpassing it in few domains. However, it is important to note (not at all)OpenAI are doing tricks with the model output. So comparing OS models with just greedy output decoding (very simple) is not fair for OS models. Still, I'm very excited this model at 13B seems to be matching falcon-40B in some benchmarks. I'm looking fo…

> OpenAI are doing tricks with the model output Do you have any pointers to the “tricks” that are being applied?

Sounds like a reference to Mixture of Experts

Re: Llama 2

#846

Post by [deleted] »

wedesoft wrote: post #831
nightski wrote: post #821

Earlier quoted context omitted.

You have to know when to stop training. How are you going to do that without a test set? How do you know when you have achieved generalization without over-fitting?

Early stopping is just one way of regularization. You can use L2 or dropout and then you can train until your model converges.

[deleted]

Re: Llama 2

#847

Post by [deleted] »

baobabKoodaa wrote: post #832
nightski wrote: post #822

Earlier quoted context omitted.

You act like training is this pre-set process you just "do". That's not the case, you train until you reach desired performance on the test set. If you don't have a test set how do you know when to stop training and avoid overfitting?

You're confusing training epochs with dataset size. I'm simplifying now, but you can think of epochs as "how many times we train over the entire dataset? 1 time? 10 times?" Correspondingly, you can think of dataset size as "how many Wikipedia pages we include in the dataset? 1 million? 10 million?" Now let's think about overfitting. What happens when you increase epochs is the model is more likely to overfit your dat…

[deleted]

Re: Llama 2

#848

Post by lucubratory »

cevn wrote: post #839
lucubratory wrote: post #687

Earlier quoted context omitted.

As always :P me and my husband will be starting our first WoT reread together (I got him into the books after he loved the show), just as soon as we finish the current series we're on, which is Children of Time by Adrian Tchaikovsky. Absolutely fantastic series.

Hm... might have to check that out as well, I love sci fi too.. Hopefully he likes the books more than the show, hah.

Children of Time is incredible, I would consider it the best sci-fi novel I've ever read in a similar way to how I consider Wheel of Time the best fantasy series I've ever read.

As for books vs show, in my opinion it's way too early to tell. Both me and him agree that the first season was significantly better than Eye Of The World, but because the later books are much better than EOTW I think the show will need to increase in quality significantly to be better than those later books - I'm excited for season 2, but in season 3 they're tackling the story of The Shadow Rising, which is probably my favourite book in the series. It's an open question in my mind if they can improve quality and characterisation enough to match that bar, although either way I'm going to enjoy it. And more importantly, I think it's not as important to judge them on a season vs book basis, because the reality is the show can't really be judged fairly against a completed book series until it is itself a completed television series. Once they're both finished (aka once I'm an old granny), I expect I'll have a much clearer idea of which rendition of the story I ultimately prefer. I know I'll definitely be talking about it with my husband a lot lol.

Re: Llama 2

#849

Post by LoganDark »

lumost wrote: post #817
LoganDark wrote: post #814

Earlier quoted context omitted.

Try GGML, llama.cpp is pretty fast

makes sense - I ultimately need to train the weights so was focusing on GPTQ, I'll try out ggml and see if the latency is better. I have some flexibility on whether I run inference/training on the same model instance. What context length were you using? I was maxing ~2048 tokens, which may also explain the apparent latency.

llama.cpp builds a prefix cache so the only latency is on the first generation :)
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