Add to the readmes for stable-lm. (#1047)

This commit is contained in:
Laurent Mazare
2023-10-06 21:26:04 +01:00
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parent d5f7267087
commit 955e00b2e8
2 changed files with 28 additions and 0 deletions

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@ -62,6 +62,8 @@ We also provide a some command line based examples using state of the art models
- [LLaMA and LLaMA-v2](./candle-examples/examples/llama/): general LLM. - [LLaMA and LLaMA-v2](./candle-examples/examples/llama/): general LLM.
- [Falcon](./candle-examples/examples/falcon/): general LLM. - [Falcon](./candle-examples/examples/falcon/): general LLM.
- [Phi-v1.5](./candle-examples/examples/phi/): a 1.3b general LLM with performance on par with LLaMA-v2 7b. - [Phi-v1.5](./candle-examples/examples/phi/): a 1.3b general LLM with performance on par with LLaMA-v2 7b.
- [StableLM-3B-4E1T](./candle-examples/examples/stable-lm/): a 3b general LLM
pre-trained on 1T tokens of English and code datasets.
- [Mistral7b-v0.1](./candle-examples/examples/mistral/): a 7b general LLM with - [Mistral7b-v0.1](./candle-examples/examples/mistral/): a 7b general LLM with
performance larger than all publicly available 13b models as of 2023-09-28. performance larger than all publicly available 13b models as of 2023-09-28.
- [StarCoder](./candle-examples/examples/bigcode/): LLM specialized to code generation. - [StarCoder](./candle-examples/examples/bigcode/): LLM specialized to code generation.
@ -152,6 +154,7 @@ If you have an addition to this list, please submit a pull request.
- StarCoder. - StarCoder.
- Phi v1.5. - Phi v1.5.
- Mistral 7b v0.1. - Mistral 7b v0.1.
- StableLM-3B-4E1T.
- T5. - T5.
- Bert. - Bert.
- Whisper (multi-lingual support). - Whisper (multi-lingual support).

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@ -0,0 +1,25 @@
# candle-stable-lm
StableLM-3B-4E1T is a 3 billion parameter decoder-only language model
pre-trained on 1 trillion tokens of diverse English and code datasets for 4
epochs. See the [HuggingFace Hub Model
Card](https://huggingface.co/stabilityai/stablelm-3b-4e1t).
Note that this model is gated so you will have to request access on the Hub in
order to be able to use it.
## Running some example
```bash
$ cargo run --example stable-lm --release --features cuda -- --prompt 'What is the most efficient programming language in use?' --sample-len 150
avx: true, neon: false, simd128: false, f16c: true
temp: 0.00 repeat-penalty: 1.10 repeat-last-n: 64
retrieved the files in 126.593µs
loaded the model in 3.474148965s
What is the most efficient programming language in use?
The answer to this question depends on what you mean by "efficient". If you're talking about speed, then C++ and Java are probably your best bets. But if you're talking about ease of development, then Python is probably the way to go.
Python is a high-level, interpreted language that is easy to learn and use. It has a large community of developers who are always working on new features and improvements.
C++ is a low-level, compiled language that can be used for both desktop applications and web development. It's more difficult to learn than Python but offers greater control over the code.
Java is another high-level language that is popular with programmers because it runs on many different platforms (including Android phones
150 tokens generated (37.61 token/s)
```