Instructions to use JJhooww/Mistral-7B-v0.2-Base_ptbr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use JJhooww/Mistral-7B-v0.2-Base_ptbr with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="JJhooww/Mistral-7B-v0.2-Base_ptbr")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("JJhooww/Mistral-7B-v0.2-Base_ptbr")
model = AutoModelForCausalLM.from_pretrained("JJhooww/Mistral-7B-v0.2-Base_ptbr", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use JJhooww/Mistral-7B-v0.2-Base_ptbr with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "JJhooww/Mistral-7B-v0.2-Base_ptbr"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "JJhooww/Mistral-7B-v0.2-Base_ptbr",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/JJhooww/Mistral-7B-v0.2-Base_ptbr

SGLang

How to use JJhooww/Mistral-7B-v0.2-Base_ptbr with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "JJhooww/Mistral-7B-v0.2-Base_ptbr" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "JJhooww/Mistral-7B-v0.2-Base_ptbr",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "JJhooww/Mistral-7B-v0.2-Base_ptbr" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "JJhooww/Mistral-7B-v0.2-Base_ptbr",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use JJhooww/Mistral-7B-v0.2-Base_ptbr with Docker Model Runner:
```
docker model run hf.co/JJhooww/Mistral-7B-v0.2-Base_ptbr
```

Adding the Open Portuguese LLM Leaderboard Evaluation Results

by leaderboard-pt-pr-bot - opened Apr 13, 2024

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+166

-3

Files changed (1) hide show

README.md +166 -3

README.md CHANGED Viewed

@@ -1,9 +1,156 @@
 ---
 license: apache-2.0
 datasets:
 - nicholasKluge/Pt-Corpus
-language:
-- pt
 ---
 É um modelo base pré-treinado com cerca de 1b tokens em portugues iniciado com os pesos oficiais do modelo, deve ser utilizado para fine tuning.
@@ -18,4 +165,20 @@ Obs: Aguardando [resultados oficiais](https://huggingface.co/spaces/eduagarcia/o
 | faquad_nli                   | 68,11             | 47,63        | 20,48    |
 | hatebr_offensive_binary      | 79,65             | 77,63        | 2,02     |
 | oab_exams                    | 45,42             | 45,24        | 0,18     |
-| portuguese_hate_speech_binary| 59,18             | 55,72        | 3,46     |

 ---
+language:
+- pt
 license: apache-2.0
 datasets:
 - nicholasKluge/Pt-Corpus
+model-index:
+- name: Mistral-7B-v0.2-Base_ptbr
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: ENEM Challenge (No Images)
+      type: eduagarcia/enem_challenge
+      split: train
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc
+      value: 64.94
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BLUEX (No Images)
+      type: eduagarcia-temp/BLUEX_without_images
+      split: train
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc
+      value: 53.96
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: OAB Exams
+      type: eduagarcia/oab_exams
+      split: train
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc
+      value: 45.42
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Assin2 RTE
+      type: assin2
+      split: test
+      args:
+        num_few_shot: 15
+    metrics:
+    - type: f1_macro
+      value: 90.11
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Assin2 STS
+      type: eduagarcia/portuguese_benchmark
+      split: test
+      args:
+        num_few_shot: 15
+    metrics:
+    - type: pearson
+      value: 72.51
+      name: pearson
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: FaQuAD NLI
+      type: ruanchaves/faquad-nli
+      split: test
+      args:
+        num_few_shot: 15
+    metrics:
+    - type: f1_macro
+      value: 69.04
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HateBR Binary
+      type: ruanchaves/hatebr
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: f1_macro
+      value: 79.62
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: PT Hate Speech Binary
+      type: hate_speech_portuguese
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: f1_macro
+      value: 58.52
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: tweetSentBR
+      type: eduagarcia/tweetsentbr_fewshot
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: f1_macro
+      value: 62.32
+      name: f1-macro
+    source:
+      url: https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=JJhooww/Mistral-7B-v0.2-Base_ptbr
+      name: Open Portuguese LLM Leaderboard
 ---
 É um modelo base pré-treinado com cerca de 1b tokens em portugues iniciado com os pesos oficiais do modelo, deve ser utilizado para fine tuning.
 | faquad_nli                   | 68,11             | 47,63        | 20,48    |
 | hatebr_offensive_binary      | 79,65             | 77,63        | 2,02     |
 | oab_exams                    | 45,42             | 45,24        | 0,18     |
+| portuguese_hate_speech_binary| 59,18             | 55,72        | 3,46     |
+# Open Portuguese LLM Leaderboard Evaluation Results
+Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/JJhooww/Mistral-7B-v0.2-Base_ptbr) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard)
+|          Metric          |  Value  |
+|--------------------------|---------|
+|Average                   |**66.27**|
+|ENEM Challenge (No Images)|    64.94|
+|BLUEX (No Images)         |    53.96|
+|OAB Exams                 |    45.42|
+|Assin2 RTE                |    90.11|
+|Assin2 STS                |    72.51|
+|FaQuAD NLI                |    69.04|
+|HateBR Binary             |    79.62|
+|PT Hate Speech Binary     |    58.52|
+|tweetSentBR               |    62.32|