Text Generation
Transformers
TensorBoard
Safetensors
French
English
gemma
SLM
french
english
Nacid
Tiny-lamina
text-generation-inference
Instructions to use Finisha-F-scratch/SMCLEM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Finisha-F-scratch/SMCLEM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Finisha-F-scratch/SMCLEM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Finisha-F-scratch/SMCLEM") model = AutoModelForCausalLM.from_pretrained("Finisha-F-scratch/SMCLEM") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Finisha-F-scratch/SMCLEM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Finisha-F-scratch/SMCLEM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Finisha-F-scratch/SMCLEM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Finisha-F-scratch/SMCLEM
- SGLang
How to use Finisha-F-scratch/SMCLEM 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 "Finisha-F-scratch/SMCLEM" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Finisha-F-scratch/SMCLEM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Finisha-F-scratch/SMCLEM" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Finisha-F-scratch/SMCLEM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Finisha-F-scratch/SMCLEM with Docker Model Runner:
docker model run hf.co/Finisha-F-scratch/SMCLEM
Update README.md
Browse files
README.md
CHANGED
|
@@ -2,10 +2,10 @@
|
|
| 2 |
library_name: transformers
|
| 3 |
tags:
|
| 4 |
- SLM
|
| 5 |
-
- french
|
| 6 |
-
- english
|
| 7 |
- Nacid
|
| 8 |
-
- Tiny-lamina
|
| 9 |
model-index:
|
| 10 |
- name: SMCLEM
|
| 11 |
results: []
|
|
@@ -14,6 +14,9 @@ language:
|
|
| 14 |
- fr
|
| 15 |
- en
|
| 16 |
pipeline_tag: text-generation
|
|
|
|
|
|
|
|
|
|
| 17 |
---
|
| 18 |
## 🏗️ Fiche Technique : SMCLEM (Small Language Clem)
|
| 19 |
|
|
@@ -43,4 +46,4 @@ Le modèle fonctionne sur un axe de **Sémantique Collisionnelle** :
|
|
| 43 |
### 🛠️ Mode d'Emploi
|
| 44 |
|
| 45 |
> **Ne pas utiliser pour :** Calculs, faits historiques, conseils médicaux ou recettes de cuisine conventionnelles.
|
| 46 |
-
> **Utiliser pour :** Briser le blocage de l'écrivain, générer des dialogues d'IA déviantes, et explorer de nouvelles syntaxes.
|
|
|
|
| 2 |
library_name: transformers
|
| 3 |
tags:
|
| 4 |
- SLM
|
| 5 |
+
- french
|
| 6 |
+
- english
|
| 7 |
- Nacid
|
| 8 |
+
- Tiny-lamina
|
| 9 |
model-index:
|
| 10 |
- name: SMCLEM
|
| 11 |
results: []
|
|
|
|
| 14 |
- fr
|
| 15 |
- en
|
| 16 |
pipeline_tag: text-generation
|
| 17 |
+
datasets:
|
| 18 |
+
- Finisha-F-scratch/Nacid
|
| 19 |
+
- NaA-IA/Tiny-lamina-data-english
|
| 20 |
---
|
| 21 |
## 🏗️ Fiche Technique : SMCLEM (Small Language Clem)
|
| 22 |
|
|
|
|
| 46 |
### 🛠️ Mode d'Emploi
|
| 47 |
|
| 48 |
> **Ne pas utiliser pour :** Calculs, faits historiques, conseils médicaux ou recettes de cuisine conventionnelles.
|
| 49 |
+
> **Utiliser pour :** Briser le blocage de l'écrivain, générer des dialogues d'IA déviantes, et explorer de nouvelles syntaxes.
|