73 lines
2.2 KiB
Markdown
73 lines
2.2 KiB
Markdown
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---
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license: bigscience-openrail-m
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library_name: transformers
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tags:
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- code
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- gpt_bigcode
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datasets:
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- nuprl/MultiPL-T
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metrics:
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- code_eval
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model-index:
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- name: MultiPLCoder-1b-OCaml
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results:
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- task:
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type: text-generation
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dataset:
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name: MultiPL-HumanEval (Lua)
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type: nuprl/MultiPL-E
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metrics:
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- type: pass@1
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value: 0.173
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name: pass@1
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verified: true
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- type: pass@1
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value: 0.113
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name: pass@1
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verified: true
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- type: pass@1
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value: 0.097
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name: pass@1
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verified: true
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---
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# MultiPLCoder-1b
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1 billion parameter version of MultiPLCoder, a set of StarCoder-based models finetuned on the [MultiPL-T dataset](https://huggingface.co/datasets/nuprl/MultiPL-T).
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These models are state-of-the-art at low-resource languages, such as: Lua, Racket, and OCaml.
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## Language Revision Index
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This is the revision index for the best-performing models for their respective langauge.
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| Langauge | Revision ID | Epoch |
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| ------------- | ----------- | ----- |
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| Lua | `7e96d931547e342ad0661cdd91236fe4ccf52545` | 3 |
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| Racket | `2cdc541bee1db4da80c0b43384b0d6a0cacca5b2` | 5 |
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| OCaml | `e8a24f9e2149cbda8c3cca264a53c2b361b7a031` | 6 |
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## Usage
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To utilize one of the models in this repository, you must first select a commit revision for that model from the table above.
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For example, to use the Lua model:
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```py
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("nuprl/MultiPLCoder-1b")
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lua_revision="7e96d931547e342ad0661cdd91236fe4ccf52545"
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model = AutoModelForCausalLM.from_pretrained("nuprl/MultiPLCoder-1b", revision=lua_revision)
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```
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Note that the model's default configuration does not enable caching, therefore you must specify to use the cache on generation.
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```py
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toks = tokenizer.encode("-- Hello World", return_tensors="pt")
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out = model.generate(toks, use_cache=True, do_sample=True, temperature=0.2, top_p=0.95, max_length=50)
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print(tokenizer.decode(out[0], skip_special_tokens=True))
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```
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```
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-- Hello World!
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-- :param name: The name of the person to say hello to
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-- :return: A greeting
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local function say_hello(name)
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return "Hello ".. name
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end
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```
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